Fix bug.

app/assets/javascripts/cancer_predict.js

@@ -327,20 +327,6 @@ $(document).ready(function(){
 				$('[for="hormone_therapy"]').css('color','');
 			};
 			/*disable_condition start*/
-      if(post_json["ER_status"] == 2 && post_json["PR_status"] == 2){
-        $('#hormone_therapy .cancer_table_btn').attr('disabled','disabled');
-        $('[for="hormone_therapy"]').css('color','rgb(204, 204, 204)');
-      }else{
-        $('#hormone_therapy .cancer_table_btn').removeAttr('disabled');
-        $('[for="hormone_therapy"]').css('color','');
-      }
-      if(post_json["HER2_status"] != 1){
-        $('#Targeted_therapy .cancer_table_btn').attr('disabled','disabled');
-        $('[for="Targeted_therapy"]').css('color','rgb(204, 204, 204)');
-      }else{
-        $('#Targeted_therapy .cancer_table_btn').removeAttr('disabled');
-        $('[for="Targeted_therapy"]').css('color','');
-      }
 			/*disable_condition end*/
 			return post_json;
 		}else{
@@ -352,7 +338,7 @@ $(document).ready(function(){
 			$('#choice_fields .cancer_table_btn').removeClass('active');
 			var load_heml = $('#result_table_content').html(result.responseJSON.table);
 			load_heml.ready(function(){
-				$('#result_table_content .cancer_years').eq(-1).addClass('active');
+				$('#result_table_content .cancer_years').eq(0).addClass('active');
 				for(var i = 0;i < $('#result_table_content .cancer_years').length;i++){
 					$('#result_table_content .cancer_years').eq(i).attr('index',i)
 				};
@@ -368,7 +354,7 @@ $(document).ready(function(){
 			});
 			load_heml = $('#result_text_content').html(result.responseJSON.texts);
 			load_heml.ready(function(){
-				$('#result_text_content .cancer_years').eq(-1).addClass('active');
+				$('#result_text_content .cancer_years').eq(0).addClass('active');
 				for(var i = 0;i < $('#result_text_content .cancer_years').length;i++){
 					$('#result_text_content .cancer_years').eq(i).attr('index',i)
 				};
@@ -405,9 +391,9 @@ $(document).ready(function(){
 				$('span.'+active_treatment[0]+'.Overall_Survival').html(Math.round(servive_ratio_arr[0]));
 				$('#cancer_predict_result_block').css('display','block');
 				var lpv_real = [result.responseJSON['lpv_variable']];
-				var lpv = /*therapy_lpv start*/[0, -0.8397, -0.4147, -0.3203, -0.4687];/*therapy_lpv end*/;
+				var lpv = /*therapy_lpv start*/[0];/*therapy_lpv end*/;
 				var lpv_dict={};
-				var lpv_calc=/*lpv_calc_formula_start*/{"1":"Math.exp(-0.001476145)**( Math.exp(lpv_current) )","3":"Math.exp(-0.01261639)**( Math.exp(lpv_current) )","5":"Math.exp(-0.02519608)**( Math.exp(lpv_current) )"};/*lpv_calc_formula_end*/
+				var lpv_calc=/*lpv_calc_formula_start*/{"1":"0.8095037**( Math.exp(lpv_current) )","1.5":"0.729158**( Math.exp(lpv_current) )","2":"0.6717211**( Math.exp(lpv_current) )","2.5":"0.6056773**( Math.exp(lpv_current) )"};/*lpv_calc_formula_end*/
 				active_treatment.push = function() {
 					if(arguments.length == 1){
 						var year = $('#current_year').attr('value');
@@ -416,7 +402,7 @@ $(document).ready(function(){
 						var lpv_current = change_object_variables(lpv_real[lpv_real.length-1],{"lpv": lpv_dict[arguments[0]]},'+');
 						lpv_real.push(lpv_current);
 						lpv_current = lpv_current['lpv'];
-						var servive_ratio = round(eval(lpv_calc[year])*100,2);
+						var servive_ratio = round((1 - eval(lpv_calc[year]))*100,2);
 						var benefit = servive_ratio - servive_ratio_arr[servive_ratio_arr.length - 1];
 						servive_ratio_arr.push(servive_ratio);
 						$('tr.'+arguments[0]+' td.Overall_Survival').html(servive_ratio+'%');
@@ -461,7 +447,7 @@ $(document).ready(function(){
 								change_object_variables(lpv_real[i] , {"lpv": lpv_dict[arguments[0]]} , '-' , 'self');
 								var lpv_current = lpv_real[i];
 								lpv_current = lpv_current['lpv'];
-								var servive_ratio = round(eval(lpv_calc[year])*100,2);
+								var servive_ratio = round((1 - eval(lpv_calc[year]))*100,2);
 								servive_ratio_arr[i] = servive_ratio;
 								var benefit = servive_ratio - ((i == index+1) ? servive_ratio_arr[index - 1] : servive_ratio_arr[i - 1]);
 								$('tr.'+active_treatment[i]+' td.Overall_Survival').html(servive_ratio+'%');
@@ -617,75 +603,135 @@ $(document).ready(function(){
       function calculate_first_lpv(result_json){
         result = {};
         var map_values , mapping_hash , temp_index ,temp_value , index , closest_value;
+        result['sex_value'] = (2 - Number(result_json['sex_value']));
         result['age'] = Number(result_json['age']);
-        result['size'] = Number(result_json['size']);
-        result['lymph_nodes_examined'] = Number(result_json['lymph_nodes_examined']);
-        result['lymph_nodes_positive'] = Number(result_json['lymph_nodes_positive']);
-        result['grade'] = Number(result_json['grade']);
-        result['ER_status'] = Number(result_json['ER_status']);
-        result['PR_status'] = Number(result_json['PR_status']);
-        result['HER2_status'] = Number(result_json['HER2_status']);
-        result['Distant_Metastasis'] = Number(result_json['Distant_Metastasis']);
-        result['micrometastasis'] = Number(result_json['micrometastasis']);
-        result['tumor_direct_extension'] = Number(result_json['tumor_direct_extension']);
-        result['lvi'] = Number(result_json['lvi']);
-        result['hormone_therapy'] = Number(result_json['hormone_therapy']);
-        result['Chemotherapy'] = Number(result_json['Chemotherapy']);
-        result['Radiotherapy'] = Number(result_json['Radiotherapy']);
-        result['Targeted_therapy'] = Number(result_json['Targeted_therapy']);
+        mapping_hash = mapping_data_from_csv['age'];
+        temp_index = 0;
+        temp_value = result['age'];
+        index = 0;
+        $.each(mapping_hash,function(k,v){
+          if( index == 0 ){
+            var index_val = v.indexOf(temp_value);
+            if( index_val != -1 ){
+              temp_index = index_val;
+            }else{
+              closest_value = v.get_nearest_value(temp_value);
+              temp_index = v.indexOf(closest_value)
+            }
+          }
+          result[k] = v[temp_index];
+          index++;
+        });
+        result['calH'] = Number(result_json['calH']);
+        mapping_hash = mapping_data_from_csv['calH'];
+        temp_index = 0;
+        temp_value = result['calH'];
+        index = 0;
+        $.each(mapping_hash,function(k,v){
+          if( index == 0 ){
+            var index_val = v.indexOf(temp_value);
+            if( index_val != -1 ){
+              temp_index = index_val;
+            }else{
+              closest_value = v.get_nearest_value(temp_value);
+              temp_index = v.indexOf(closest_value)
+            }
+          }
+          result[k] = v[temp_index];
+          index++;
+        });
+        result['calAH'] = Number(result_json['calAH']);
+        mapping_hash = mapping_data_from_csv['calAH'];
+        temp_index = 0;
+        temp_value = result['calAH'];
+        index = 0;
+        $.each(mapping_hash,function(k,v){
+          if( index == 0 ){
+            var index_val = v.indexOf(temp_value);
+            if( index_val != -1 ){
+              temp_index = index_val;
+            }else{
+              closest_value = v.get_nearest_value(temp_value);
+              temp_index = v.indexOf(closest_value)
+            }
+          }
+          result[k] = v[temp_index];
+          index++;
+        });
+        result['calDH'] = Number(result_json['calDH']);
+        mapping_hash = mapping_data_from_csv['calDH'];
+        temp_index = 0;
+        temp_value = result['calDH'];
+        index = 0;
+        $.each(mapping_hash,function(k,v){
+          if( index == 0 ){
+            var index_val = v.indexOf(temp_value);
+            if( index_val != -1 ){
+              temp_index = index_val;
+            }else{
+              closest_value = v.get_nearest_value(temp_value);
+              temp_index = v.indexOf(closest_value)
+            }
+          }
+          result[k] = v[temp_index];
+          index++;
+        });
+        result['fat'] = Number(result_json['fat']);
+        mapping_hash = mapping_data_from_csv['fat'];
+        temp_index = 0;
+        temp_value = result['fat'];
+        index = 0;
+        $.each(mapping_hash,function(k,v){
+          if( index == 0 ){
+            var index_val = v.indexOf(temp_value);
+            if( index_val != -1 ){
+              temp_index = index_val;
+            }else{
+              closest_value = v.get_nearest_value(temp_value);
+              temp_index = v.indexOf(closest_value)
+            }
+          }
+          result[k] = v[temp_index];
+          index++;
+        });
+        result['N4'] = (2 - Number(result_json['N4']));
+        result['N12'] = (2 - Number(result_json['N12']));
+        result['N20'] = (2 - Number(result_json['N20']));
+        result['N31'] = (2 - Number(result_json['N31']));
+        result['O6'] = (2 - Number(result_json['O6']));
+        result['N34'] = (2 - Number(result_json['N34']));
+        result['N14'] = (2 - Number(result_json['N14']));
+        result['N26'] = (2 - Number(result_json['N26']));
+        result['O3'] = (2 - Number(result_json['O3']));
+        result['O20'] = (2 - Number(result_json['O20']));
+        result['O18'] = (2 - Number(result_json['O18']));
+        result['O11'] = (2 - Number(result_json['O11']));
+        result['N29'] = (2 - Number(result_json['N29']));
+        result['N6'] = (2 - Number(result_json['N6']));
+        result['O14'] = (2 - Number(result_json['O14']));
+        result['N43'] = (2 - Number(result_json['N43']));
+        result['O17'] = (2 - Number(result_json['O17']));
+        result['O9'] = (2 - Number(result_json['O9']));
 
         Object.keys(result).forEach(function(k){
           if(Number.isNaN(result[k])){
             result[k] = 0;
           }
         })
-        age1 = (result["age"] / 100.0) ** (0.5);
-        age2 = age1 * Math.log(result["age"] / 100.0);
-        size1 = Math.log(result["size"] / 10.0);
-        ratio = (result["lymph_nodes_examined"] == 0 ? 0 : (1.0 * result["lymph_nodes_positive"] / result["lymph_nodes_examined"]));
-        ratio = (ratio > 1 ? 1 : ratio);
-        T4 = (result["tumor_direct_extension"] == 1);
-        T1 = !T4 && (result["size"] <= 20);
-        T2 = !T4 && !T1 && (result["size"] > 20 && result["size"] <= 50);
-        T = (T4 ? 'T4' : (T1 ? 'T1' : (T2 ? 'T2' : 'T3')));
-        N0 = (result["lymph_nodes_positive"] == 0);
-        N1_or_N1mi = !N0 && (result["lymph_nodes_positive"] >= 1 && result["lymph_nodes_positive"] <= 3);
-        N1 = N1_or_N1mi && result["micrometastasis"] != 1;
-        N1mi = N1_or_N1mi && result["micrometastasis"] == 1;
-        N2 = !N0 && !N1_or_N1mi && (result["lymph_nodes_positive"] <= 9);
-        N = (N0 ? 'N0' : (N1 ? 'N1' : (N1mi ? 'N1mi' : (N2 ? 'N2' : 'N3'))));
-        M = (result["Distant_Metastasis"] != 1) ? 'M0' : 'M1';
-        pstage = (M == 'M1' ? 4 : ((T == 'T1' && (N == 'N0' || N == 'N1mi')) ? 1 : (((T == 'T2' || T == 'T3') && (N == 'N0')) || ((T == 'T1' || T == 'T2') && (N == 'N1')) ? 2 : 3)) );
-        nposit = ((ratio + 0.1) / 0.1) ** 0.5;
-        grade_2 = (result["grade"] == 2 || result["grade"] == 4) ? 1 : 0;
-        grade_3 = (result["grade"] == 3) ? 1 : 0;
-        subtype_1 = (result["ER_status"] != 2 || result["PR_status"] != 2) && (result["HER2_status"] != 1);
-        subtype_2 = !subtype_1 && (result["HER2_status"] == 1);
-        subtype_3 = !subtype_1 && !subtype_2 && (result["ER_status"] == 2 && result["PR_status"] == 2 && result["HER2_status"] != 1);
-        subtype_HER2 = subtype_2 ? 1 : 0;
-        subtype_triple = subtype_3 ? 1 : 0;
-        pstage_2 = (pstage == 2) ? 1 : 0;
-        pstage_3 = (pstage == 3) ? 1 : 0;
-        pstage_4 = (pstage == 4) ? 1 : 0;
-        lvi_yes = (result["lvi"] == 1) ? 1 : 0;
-        chemo = (result["Chemotherapy"] == 2) ? 1 : 0;
-        radio = (result["Radiotherapy"] == 2) ? 1 : 0;
-        hormone = (result["hormone_therapy"] == 2) ? 1 : 0;
-        target = (result["Targeted_therapy"] == 2) ? 1 : 0;
+        ;
         try{
-          lpv = ((age1-0.7276655)*(-10.87)+(age2+0.4540707)*8.968+(size1-0.643632)*0.7678+(nposit-1.346932)*0.5339+ grade_2*0.4795+grade_3*0.818+subtype_HER2*0.1806+subtype_triple*0.6457+pstage_2*0.5311+ pstage_3*1.134+pstage_4*2.172+lvi_yes*0.3321-0.04+chemo*(-0.4147)+radio*(-0.3203)+hormone*(-0.8397)+target*(-0.4687)
-          )
+          A = 0.1327868* (result["sex_value"]- 0.4858824) + 0.0371720* (result["age_test1"] - 61.56000) -0.07447278* (result["age_test2"] - 13.10152) + 0.4315686* (result["age_test3"] - 0.9844332) + 0.0009163615*( result["calH_test1"] - 182.9347) -0.0007536899*( result["calH_test2"] - 124.8706) -0.00004697183*( result["calH_test3"] -80.75636) + 0.0001401325*( result["calAH_test1"] - 700.7824)  -0.001349783*( result["calAH_test2"] - 634.2167) +0.001753832*( result["calAH_test3"] -419.3361) + 0.0001906046*( result["calDH_test1"] -835.2894) -0.000251567*( result["calDH_test2"] - 213.1630)  -0.002173942*( result["fat_test1"] -108.4149)+0.003066541*( result["fat_test2"] - 28.33497) +0.6700708*(result["N4"]-0.3241176) +0.3336162*(result["O3"]-0.4994118) +0.1322476*(result["O20"]-0.1741176) +0.9084972*(result["O18"]-0.008823529) +0.2978388*(result["N12"]-0.1152941) +0.1777935*(result["N20"]-0.3582353) +1.588042*(result["N31"]-0.002352941) +0.2197419*(result["O6"]-0.07823529) +1.791159*(result["N34"]-0.001176471) +0.4305973*(result["N14"]-0.02176471) -0.4472885*(result["N29"]-0.02411765) +0.2601319*(result["N26"]-0.04941176) -0.2364269*(result["O11"]-0.1164706) +0.1784179*(result["N6"]-0.1070588) +0.6023170*(result["O14"]-0.01294118) -1.031959*(result["N43"]-0.007058824) +0.4257809*(result["O17"]-0.01823529) +0.2002546*(result["O9"]-0.06176471)
         }catch(e){console.log(e)};
         result['lpv_variable'] = {};
-        result['lpv_variable']['lpv'] = lpv;
-        result['lpv'] = lpv;
+        result['lpv_variable']['A'] = A;
+        result['lpv'] = A;
         result['lpv_variable']['lpv'] = result['lpv'];
         return result;
       };
       function calculate_and_change_result_value(obj){
         obj.servive_ratio_arr = [];
         for(var i = 0;i<obj.active_treatment.length;i++){
-          var servive_ratio = round(calculate_servive_ratio(obj.year,obj.lpv_real[i])*100,2);
+          var servive_ratio = round((1 - calculate_servive_ratio(obj.year,obj.lpv_real[i]))*100,2);
           var benefit = servive_ratio - obj.servive_ratio_arr[obj.servive_ratio_arr.length-1];
           obj.servive_ratio_arr.push(servive_ratio);
           $('tr.'+obj.active_treatment[i]+' td.Overall_Survival').html(servive_ratio+'%');
@@ -700,16 +746,19 @@ $(document).ready(function(){
 
     function calculate_servive_ratio(year,obj){
       var servive_ratio;
-      var lpv = obj['lpv'];
+      var A = obj['A'];
       switch(year) {
         case  '1':
-          servive_ratio = Math.exp(-0.001476145)**( Math.exp(lpv) );
+          servive_ratio = 0.8095037**( Math.exp(A) );
           break;
-        case  '3':
-          servive_ratio = Math.exp(-0.01261639)**( Math.exp(lpv) );
+        case  '1.5':
+          servive_ratio = 0.729158**( Math.exp(A) );
           break;
-        case  '5':
-          servive_ratio = Math.exp(-0.02519608)**( Math.exp(lpv) );
+        case  '2':
+          servive_ratio = 0.6717211**( Math.exp(A) );
+          break;
+        case  '2.5':
+          servive_ratio = 0.6056773**( Math.exp(A) );
           break;
         default:
           console.log('not found year.');

app/controllers/cancerpredicts_controller.rb

@@ -1,227 +1,221 @@
 # encoding: utf-8
-require "rubyXL"
+require 'rubyXL'
 require "json"
-
 class CancerpredictsController < ApplicationController
   def initialize
     super
     @app_title = "cancerpredict"
   end
-
   def calculate
-    create_first_field
-    if params["header"].to_i == 1
-      locale = params["locale"].to_s rescue "zh_tw"
-      locale = "zh_tw" if locale == "zh_cn"
-      result = {}
-      @head_images = {}
-      @form_to_show.head_images_id.each do |image_id|
-        next if image_id.to_s == ""
-        @image = Headimages.find_by(:id => image_id.to_s)
-        @url = @image.temp_file.to_s
-        @head_images[@image.sort_number.to_i] = ('<img class="head_logo" alt ="' + Pathname.new(@image.temp_file.file.file).basename.to_s + '" src="' + @url + '"/>')
-      end
-      result["head_images"] = Hash[@head_images.sort].values.join("")
-      @head_images = {}
-      @form_to_show.title_images_id.each do |image_id|
-        next if image_id.to_s == ""
-        @image = Headimages.find_by(:id => image_id.to_s)
-        @url = @image.temp_file.to_s
-        @head_images[@image.sort_number.to_i] = ('<img class="head_logo" alt ="' + Pathname.new(@image.temp_file.file.file).basename.to_s + '" src="' + @url + '"/>')
-      end
-      result["danger_texts"] = (@form_to_show.danger_texts[locale] rescue "")
-      result["title"] = Hash[@head_images.sort].values.join("")
-      result["page_title"] = @form_to_show.title_texts[params[:locale]]
-    elsif params["get_mapping_data_from_csv"].to_i == 1
-      result = {}
-      result["mapping_data_from_csv"] = JSON.parse(@form_to_show.mapping_data_from_csv) rescue {}
-    else
-      @record = Cancerpredictrecord.new
-      @record.title = @app_title
-      @choice_keys = []
-      @choice_values = []
-      @choice_names = []
-      @form_to_show.form_show.values.each { |choice| @choice_keys.push choice[:variable] }
-      @form_to_show.form_show.values.each { |choice| @choice_values.push ((choice[:is_num] == 1) ? [] : choice[:choice_fields]) }
-      @form_to_show.form_show.values.each { |choice| @choice_names.push choice[:name] }
-      @choice_keys.each_with_index { |key, i| @record.names[key] = @choice_names[i] }
-      @choice_keys.each_with_index { |key, i| @record.values[key] = @choice_values[i] }
-      params["data"].each do |rec_key, rec_value|
-        @record.result[rec_key] = rec_value
-      end
-      @record.submit_time = Time.now.to_s
-      @record.save
-      locale = params["data"]["locale"].to_s rescue "zh_tw"
-      locale = "zh_tw" if locale == "zh_cn"
-      result = {}
-      mapping_data_from_csv = JSON.parse(@form_to_show.mapping_data_from_csv) rescue {}
-      @form_to_show.all_variables.each do |v|
-        result[v] = 0
-      end
-      @form_to_show.form_show.each do |num, property|
-        @variable = property[:variable]
-        if @variable.present?
-          if property[:is_num] == 1
-            if property[:is_float] == 1
-              result[@variable] = params["data"][@variable].to_f rescue 0.0
-            else
-              result[@variable] = params["data"][@variable].to_i rescue 0
-            end
-          elsif property[:choice_fields].present?
-            if !(@form_to_show.advance_mode)
-              result[@variable] = params["data"][@variable].to_i rescue 0
-            else
-              if property[:need_map_values] == 1
-                result[@variable] = property[:map_values][params["data"][@variable].to_i - 1]
-              else
-                if property[:revert_value] != 1
-                  result[@variable] = params["data"][@variable].to_i - 1
-                else
-                  result[@variable] = ((property[:choice_fields].length - params["data"][@variable].to_i) rescue params["data"][@variable].to_i)
-                end
-              end
-            end
-          end
-          if @form_to_show.advance_mode && property[:cancer_predict_mapping_file].present?
-            if (mapping_data_from_csv != {})
-              mapping_hash = mapping_data_from_csv[@variable]
-              temp_index = 0
-              temp_value = result[@variable]
-              mapping_hash.each_with_index do |(k, v), i|
-                if i == 0
-                  index_val = v.index(temp_value) rescue nil
-                  if !index_val.nil?
-                    temp_index = index_val
-                  else
-                    closest_value = v.min_by { |x| (temp_value - x).abs }
-                    temp_index = v.index(closest_value)
-                  end
-                end
-                result[k] = v[temp_index]
-              end
-            end
-          end
-        end
-      end
-      formula_variables = @form_to_show.tmp_lpv_variables
-      begin
-        eval_hidden_variables(result)
-      rescue => e
-        @form_to_show.generate_eval_formula
-        eval_hidden_variables(result)
-      end
-      begin
-        eval_formula(result)
-      rescue => e
-        @form_to_show.generate_eval_formula
-        eval_formula(result)
-      end
-      result["lpv"] = result[formula_variables.last]
-      result["lpv_variable"] = {}
-      formula_variables.each do |variable_name|
-        result["lpv_variable"]["#{variable_name}"] = result[variable_name]
-      end
-      @years = @form_to_show.years
-      result["years"] = @years
-      @therapy_choices = [I18n.t("cancerpredict.table.Surgeryonly")]
-      @form_to_show.form_show_in_result.values.each { |choice| @therapy_choices.push choice["name"][locale] }
-      @therapy_names = @form_to_show.treatment_method
-      result["treatment_method"] = @therapy_names
-      result["treatment_method_active_indices"] = @form_to_show.treatment_method_active_indices
-      result["table"] = @form_to_show.result_table_translations[locale]
-      year = params["data"]["year"] rescue nil
-      if year.nil?
-        year = @years.last.to_f
-      else
-        year = year.to_f
-      end
-      year_index = @years.index(year)
-      @servive_ratio = eval(@form_to_show.tmp_years_settings_for_ruby[year_index])
-      @servive_ratio = (@servive_ratio * 100).round(2)
-      result["texts"] = @form_to_show.result_text_translations[locale]
-      result["extra_therapy_texts"] = @form_to_show.extra_therapy_texts[locale] rescue @form_to_show.extra_therapy_texts["zh_tw"]
-      result["servive_ratio"] = @servive_ratio
-    end
-    result = result.merge(params)
-    render :json => result
+	create_first_field
+	if params['header'].to_i == 1
+		locale = params['locale'].to_s rescue 'zh_tw'
+		locale = 'zh_tw' if locale == 'zh_cn'
+		result = {}
+		@head_images =  {}
+		@form_to_show.head_images_id.each do |image_id|
+			next if image_id.to_s == ""
+			@image = Headimages.find_by(:id=>image_id.to_s)
+			@url = @image.temp_file.to_s
+			@head_images[@image.sort_number.to_i] = ('<img class="head_logo" alt ="' + Pathname.new(@image.temp_file.file.file).basename.to_s+'" src="'+@url+'"/>')
+		end
+		result['head_images'] = Hash[@head_images.sort].values.join('')
+		@head_images =  {}
+		@form_to_show.title_images_id.each do |image_id|
+			next if image_id.to_s == ""
+			@image = Headimages.find_by(:id=>image_id.to_s)
+			@url = @image.temp_file.to_s
+			@head_images[@image.sort_number.to_i] = ('<img class="head_logo" alt ="' + Pathname.new(@image.temp_file.file.file).basename.to_s+'" src="'+@url+'"/>')
+		end
+		result['danger_texts'] = (@form_to_show.danger_texts[locale] rescue '')
+		result['title'] = Hash[@head_images.sort].values.join('')
+		result['page_title'] = @form_to_show.title_texts[params[:locale]]
+	elsif params['get_mapping_data_from_csv'].to_i == 1
+		result = {}
+		result['mapping_data_from_csv'] = JSON.parse(@form_to_show.mapping_data_from_csv) rescue {}
+	else
+		@record = Cancerpredictrecord.new
+		@record.title = @app_title
+		@choice_keys = []
+		@choice_values = []
+		@choice_names = []
+		@form_to_show.form_show.values.each{|choice| @choice_keys.push choice[:variable]}
+		@form_to_show.form_show.values.each{|choice| @choice_values.push ((choice[:is_num] == 1) ? [] : choice[:choice_fields])}
+		@form_to_show.form_show.values.each{|choice| @choice_names.push choice[:name]}
+		@choice_keys.each_with_index{|key,i| @record.names[key] = @choice_names[i]}
+		@choice_keys.each_with_index{|key,i| @record.values[key] = @choice_values[i]}
+		params['data'].each do |rec_key,rec_value| 
+			@record.result[rec_key] = rec_value
+		end
+		@record.submit_time = Time.now.to_s
+		@record.save
+		locale = params['data']['locale'].to_s rescue 'zh_tw'
+		locale = 'zh_tw' if locale == 'zh_cn'
+		result = {}
+		mapping_data_from_csv = JSON.parse(@form_to_show.mapping_data_from_csv) rescue {}
+		@form_to_show.all_variables.each do |v|
+			result[v] = 0
+		end
+		@form_to_show.form_show.each do |num,property|
+			@variable = property[:variable]
+			if @variable.present?
+				if property[:is_num] == 1
+					if property[:is_float] == 1
+						result[@variable] = params['data'][@variable].to_f rescue 0.0
+					else
+						result[@variable] = params['data'][@variable].to_i rescue 0
+					end
+				elsif property[:choice_fields].present?
+					if !(@form_to_show.advance_mode)
+						result[@variable] = params['data'][@variable].to_i rescue 0
+					else
+						if property[:need_map_values] == 1
+							result[@variable] = property[:map_values][params['data'][@variable].to_i - 1]
+						else
+							if property[:revert_value] != 1
+								result[@variable] = params['data'][@variable].to_i - 1
+							else
+								result[@variable] = ((property[:choice_fields].length - params['data'][@variable].to_i) rescue params['data'][@variable].to_i)
+							end
+						end
+					end
+				end
+				if @form_to_show.advance_mode && property[:cancer_predict_mapping_file].present?
+					if (mapping_data_from_csv != {})
+						mapping_hash = mapping_data_from_csv[@variable]
+						temp_index = 0
+						temp_value = result[@variable]
+						mapping_hash.each_with_index do |(k,v),i|
+							if i == 0
+								index_val = v.index(temp_value) rescue nil
+								if !index_val.nil?
+									temp_index = index_val
+								else 
+									closest_value = v.min_by{|x| (temp_value-x).abs}
+									temp_index = v.index(closest_value)
+								end
+							end
+							result[k] = v[temp_index]
+						end
+					end
+				end
+			end
+		end
+		formula_variables = @form_to_show.tmp_lpv_variables
+		begin
+			eval_hidden_variables(result)
+		rescue => e
+			@form_to_show.generate_eval_formula
+			eval_hidden_variables(result)
+		end
+		begin
+			eval_formula(result)
+		rescue => e
+			@form_to_show.generate_eval_formula
+			eval_formula(result)
+		end
+		result['lpv'] = result[formula_variables.last]
+		result['lpv_variable'] = {}
+		formula_variables.each do |variable_name|
+			result['lpv_variable']["#{variable_name}"] = result[variable_name]
+		end
+		@years = @form_to_show.years
+		result['years'] = @years
+		@therapy_choices = [I18n.t('cancerpredict.table.Surgeryonly')]
+		@form_to_show.form_show_in_result.values.each{|choice| @therapy_choices.push choice["name"][locale]}
+		@therapy_names = @form_to_show.treatment_method
+		result['treatment_method'] = @therapy_names
+		result['treatment_method_active_indices'] = @form_to_show.treatment_method_active_indices
+		result['table'] = @form_to_show.result_table_translations[locale]
+		year = params['data']['year'] rescue nil
+		if year.nil?
+			year = @years.first.to_f
+		else
+			year = year.to_f
+		end
+		year_index = @years.index(year)
+		@servive_ratio = eval(@form_to_show.tmp_years_settings_for_ruby[year_index])
+		@servive_ratio = ((1 - @servive_ratio) * 100).round(2)
+		result['texts'] = @form_to_show.result_text_translations[locale]
+		result['extra_therapy_texts'] = @form_to_show.extra_therapy_texts[locale] rescue @form_to_show.extra_therapy_texts['zh_tw']
+		result['servive_ratio'] = @servive_ratio
+	end
+	result = result.merge(params)
+	render :json=> result
   end
-
   def index
-    uid = OrbitHelper.params[:uid] rescue ""
-    tags = OrbitHelper.widget_tags
-    categories = OrbitHelper.widget_categories || []
-    @table_str = File.read(Cancerpredictfields::ToolTableMap[I18n.locale])
-    preidct_js_url = "/assets/#{Cancerpredictfields::JS}"
-    if File.exist?(Cancerpredictfields::JSFileName)
-      js_filename = File.read(Cancerpredictfields::JSFileName)
-      if js_filename.include?(Cancerpredictfields::JS)
-        asset = Rails.application.assets[js_filename]
-        preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
-      else
-        preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
-      end
-    end
-    {
-      "cancerpredict" => [],
-      "extras" => { "table" => @table_str, "preidct_js_url" => preidct_js_url },
-    }
+	uid = OrbitHelper.params[:uid] rescue ""
+	tags = OrbitHelper.widget_tags
+	categories = OrbitHelper.widget_categories || []
+	@table_str = File.read('public/cancer_tool_table_tmp_'+I18n.locale.to_s+'.txt')
+	preidct_js_url = '/assets/cancer_predict.js'
+	if File.exist?('public/cancer_tool_js_filename.txt')
+		js_filename = File.read('public/cancer_tool_js_filename.txt')
+		if js_filename.match(/cancer_predict\.js$/)
+			asset = Rails.application.assets[js_filename]
+			preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
+		else
+			preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
+		end
+	end
+	{
+	  "cancerpredict" => [],
+	  "extras"=>{"table"=> @table_str,'preidct_js_url'=>preidct_js_url}
+	}
   end
-
   def widget
-    uid = OrbitHelper.params[:uid] rescue ""
-    tags = OrbitHelper.widget_tags
-    categories = OrbitHelper.widget_categories || []
-    @table_str = File.read(Cancerpredictfields::ToolTableMap[I18n.locale])
-    preidct_js_url = "/assets/#{Cancerpredictfields::JS}"
-    if File.exist?(Cancerpredictfields::JSFileName)
-      js_filename = File.read(Cancerpredictfields::JSFileName)
-      if js_filename.include?(Cancerpredictfields::JS)
-        asset = Rails.application.assets[js_filename]
-        preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
-      else
-        preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
-      end
-    end
-    {
-      "cancerpredict" => [],
-      "extras" => { "table" => @table_str, "preidct_js_url" => preidct_js_url },
-    }
+	uid = OrbitHelper.params[:uid] rescue ""
+	tags = OrbitHelper.widget_tags
+	categories = OrbitHelper.widget_categories || []
+	@table_str = File.read('public/cancer_tool_table_tmp_'+I18n.locale.to_s+'.txt')
+	preidct_js_url = '/assets/cancer_predict.js'
+	if File.exist?('public/cancer_tool_js_filename.txt')
+		js_filename = File.read('public/cancer_tool_js_filename.txt')
+		if js_filename.match(/cancer_predict\.js$/)
+			asset = Rails.application.assets[js_filename]
+			preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
+		else
+			preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
+		end
+	end
+	{
+	  "cancerpredict" => [],
+	  "extras"=>{"table"=> @table_str,'preidct_js_url'=>preidct_js_url}
+	}
   end
-
   def create_first_field
-    if Cancerpredictfields.where("title" => (@app_title + "_back")).count == 0
-      @form_to_show = Cancerpredictfields.new()
-      @form_to_show.title = @app_title + "_back"
-      @form_to_show.save
-    end
-    @form_to_show
-    if Cancerpredictfields.where("title" => @app_title).count == 0
-      @form_to_show = Cancerpredictfields.new()
-      @form_to_show.title = @app_title
-      @form_to_show.save
-      @form_to_show = Cancerpredictfields.where("title" => @app_title).first
-    else
-      @form_to_show = Cancerpredictfields.where("title" => @app_title).first
-    end
+	if Cancerpredictfields.where("title"=>(@app_title + "_back")).count == 0
+		@form_to_show = Cancerpredictfields.new()
+		@form_to_show.title = @app_title +"_back"
+		@form_to_show.save
+	end
+	@form_to_show
+	if Cancerpredictfields.where("title"=>@app_title).count == 0
+		@form_to_show = Cancerpredictfields.new()
+		@form_to_show.title=@app_title
+		@form_to_show.save
+		@form_to_show = Cancerpredictfields.where("title"=>@app_title).first
+	else
+		@form_to_show = Cancerpredictfields.where("title"=>@app_title).first
+	end
   end
-
   def read_mapping_file(mapping_file)
-    if mapping_file.class != CancerPredictMappingFile
-      mapping_file = CancerPredictMappingFile.find(mapping_file_id) rescue nil
-    end
-    if !mapping_file.nil?
-      csv_rows = CSV.read(mapping_file.temp_file.file.path)
-      titles = csv_rows[0]
-      infos = {}
-      titles.each_with_index do |title, i|
-        infos[title] = []
-        csv_rows[1..-1].each do |row|
-          infos[title] << row[i].to_f
-        end
-      end
-      return infos
-    else
-      return {}
-    end
+  	if mapping_file.class != CancerPredictMappingFile
+  		mapping_file = CancerPredictMappingFile.find(mapping_file_id) rescue nil
+  	end
+  	if !mapping_file.nil?
+  		csv_rows = CSV.read(mapping_file.temp_file.file.path)
+  		titles = csv_rows[0]
+  		infos = {}
+  		titles.each_with_index do |title,i|
+  			infos[title] = []
+  			csv_rows[1..-1].each do |row|
+  				infos[title] << row[i].to_f
+  			end
+  		end
+  		return infos
+  	else
+  		return {}
+  	end
   end
 end

app/helpers/admin/cancerpredicts_helper.rb

@@ -1,13 +1,4 @@
 module Admin::CancerpredictsHelper
-	def bc_yaml_dump(arr)
-		if arr.blank?
-			'[]'
-		elsif arr.class != String
-			'[' + arr.map{|s| (s.is_a?(String) && !(s.is_i?) && s.include?(' ')) ? "\"#{s}\"" : s}.join(', ') + ']'
-		else
-			arr
-		end
-	end
 	def create_pagination(page=1,fields=Cancerpredictrecord.all,extra_params="")
 		page = 1 if page == 0
 		per_page_num = 10.0

app/models/cancerpredictfields.rb

@@ -9,95 +9,112 @@ class Cancerpredictfields
   AdvanceFields = ["revert_value","map_values","cancer_predict_mapping_file"]
   TherapyFields = ["variable","name","hint","comment_text","choice_fields","lpv_impact","active_choice","disable_condition"]
   TherapyOnly = ["lpv_impact","active_choice","disable_condition"]
-  JSFileName = "public/cancer_tool_js_filename.txt".freeze
-  ModuleAppPath = Pathname.new(File.expand_path(__dir__)).dirname.dirname.to_s.freeze
-  JS = "cancer_predict.js"
-  ToolTableMap = I18n.available_locales.map do |locale|
-    [locale, "public/cancer_tool_table_tmp_#{locale}.txt".freeze]
-  end.to_h
   field :title ,type:String ,default:""
-  field :advance_mode, type: Boolean, default: false
+  field :advance_mode, type: Boolean, default: true
   field :form_show ,  :type=> Hash ,default:{
-                            "0"=>{"variable"=>"age", "name"=>{"zh_tw"=>"年齡<br/>(Age)", "en"=>"Age"}, "is_num"=>1, "hint"=>{"zh_tw"=>"從 18 歲(含)開始至 93 歲", "en"=>"Age must be between 18 and 93"}, "comment_text"=>{"zh_tw"=>"年齡為該婦女於確診罹患乳癌時之年齡", "en"=>"Age at diagnosis"}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[18, 93], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "1"=>{"variable"=>"size", "name"=>{"zh_tw"=>"腫瘤大小(單位:mm)<br/>(Tumor size)", "en"=>"Tumor size"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>"The unit of tumor size is millimeter (mm)"}, "comment_text"=>{"zh_tw"=>"若有多個原發腫瘤，請輸入最大尺寸之原發腫瘤", "en"=>"If there was more than one primary tumor, please enter the size of the largest one."}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[1, 300], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "2"=>{"variable"=>"lymph_nodes_examined", "name"=>{"zh_tw"=>"區域淋巴結檢查數目<br/>(Regional lymph nodes examined)", "en"=>"Regional lymph nodes examined"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["未知"], "en"=>["unknown"]}, "range"=>[0, 90], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "3"=>{"variable"=>"lymph_nodes_positive", "name"=>{"zh_tw"=>"區域淋巴結侵犯數目<br/>(Regional lymph nodes positive)", "en"=>"Regional lymph nodes positive"}, "is_num"=>1, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"此變項為預測重要變數，若無此資訊預測容易失真。", "en"=>"Regional lymph nodes positive is a key predictive variable. If this information is omitted, the prediction result would be biased."}, "choice_fields"=>{"zh_tw"=>["未知"], "en"=>["unknown"]}, "range"=>[0, 90], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "4"=>{"variable"=>"grade", "name"=>{"zh_tw"=>"腫瘤分化程度<br/>(Tumor grade)", "en"=>"Tumor grade"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"腫瘤級數代表腫瘤組織與正常組織間的分化程度，若無分化級數資訊，請選擇“未知”選項，將以級數 2 進行預測。", "en"=>"The grade refers to how different the cancer cells are from normal cells. Please select “unknown” if there is no information about grade. The prediction model would use “grade 2” as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["1", "2", "3", "未知"], "en"=>["1", "2", "3", "unknown"]}, "range"=>[], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "5"=>{"variable"=>"ER_status", "name"=>{"zh_tw"=>"ER 狀態<br/>(ER status)", "en"=>"ER status"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"ER:雌激素受體，若無 ER 資訊請選擇未知，將以佔多數比例陽 性作為後續預測。", "en"=>"ER status describes the status of estrogen receptor. Please select “unknown” if there is no information about ER status. The prediction model would use “Positive” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["陽性", "陰性", "未知"], "en"=>["positive", "negative", "unknown"]}, "range"=>[], "right"=>0, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "6"=>{"variable"=>"PR_status", "name"=>{"zh_tw"=>"PR 狀態<br/>(PR status)", "en"=>"PR status"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"PR:黃體素受體， 若無 PR 資訊請選擇未知，將以佔多數比例陽性作為後續預測。", "en"=>"PR status describes the status of progesterone receptor. Please select  “unknown” if there is no information about PR status. The prediction model would use “Positive” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["陽性", "陰性", "未知"], "en"=>["positive", "negative", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "7"=>{"variable"=>"HER2_status", "name"=>{"zh_tw"=>"HER2 狀態<br/>(HER2 status)", "en"=>"HER2 status"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"HER2:第二型人類上皮成長因子接受器蛋白，若無 HER2 資訊請選擇未知，將以佔多數比例陰性作為後續預測。", "en"=>"HER2 status describes the status of human epidermal growth factor receptor 2. Please select “unknown” if there is no information about HER2 status. The prediction model would use “Negative” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["陽性", "陰性", "未知"], "en"=>["positive", "negative", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "8"=>{"variable"=>"Distant_Metastasis", "name"=>{"zh_tw"=>"遠端轉移<br/>(Distant Metastasis)", "en"=>"Distant Metastasis"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"若無遠端轉移資訊請選擇未知，將以佔多數比例未遠端轉移作為後續預測。", "en"=>"Please select “unknown” if there is no information about distant Metastasis. The prediction model would use “No” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["是", "否", "未知"], "en"=>["yes", "no", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "9"=>{"variable"=>"micrometastasis", "name"=>{"zh_tw"=>"淋巴結顯微轉移<br/>(Lymph nodes micrometastasis)", "en"=>"Micrometastasis"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"若無顯微移資訊請選擇未知，將以無顯微轉移作為後續預測。", "en"=>"Please select “unknown” if there is no information about lymph nodes micrometastasis. The prediction model would use “No” as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["是", "否", "未知"], "en"=>["yes", "no", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "10"=>{"variable"=>"tumor_direct_extension", "name"=>{"zh_tw"=>"腫瘤浸潤至胸壁和/或皮膚<br/>(Tumor direct extension to the chest wall and/or to the skin)", "en"=>"Tumor direct extension to the chest wall and/or to the skin"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"若無腫瘤浸潤至胸壁或皮膚資訊請選擇未知，將以佔多數比例無腫瘤浸潤至胸壁作為後續預測。", "en"=>"Please select “unknown” if there is no information about tumor direct extension to the chest wall and/or to the skin. The prediction model would use “No” (the majority class) as the alternative variable"}, "choice_fields"=>{"zh_tw"=>["是", "否", "未知"], "en"=>["yes", "no", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]},
-                            "11"=>{"variable"=>"lvi", "name"=>{"zh_tw"=>"淋巴管或血管侵犯<br/>(Lymph vessel or vascular invasion, LVI)", "en"=>"Lymph vessel or vascular invasion, LVI"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>"Lymph vessel or vascular invasion"}, "comment_text"=>{"zh_tw"=>"若無淋巴管或血管侵犯資訊，請選擇“未知”選項，將以佔多數比例的淋巴管或血管未侵犯進行預測", "en"=>"Please select “unknown” if there is no information about Lymph vessel or vascular invasion. The prediction model would use “No” (the majority class) as the alternative variable."}, "choice_fields"=>{"zh_tw"=>["是", "否", "未知"], "en"=>["yes", "no", "unknown"]}, "range"=>[], "right"=>1, "is_float"=>0, "need_map_values"=>0, "revert_value"=>0, "map_values"=>[]}
-                          }
-  field :form_show_in_result ,  :type=> Hash ,default: {
-                            "0"=>{"variable"=>"hormone_therapy", "name"=>{"zh_tw"=>"賀爾蒙治療", "en"=>"Hormone/Steroid therapy"}, "is_num"=>0, "hint"=>{"zh_tw"=>"適用賀爾蒙受體陽性病人", "en"=>"Hormone/ steroid therapy is available when ER status is positive"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["否", "是"], "en"=>["No", "Yes"]}, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>0, "map_values"=>"", "active_choice"=>2, "disable_condition"=>"ER_status == 2 && PR_status == 2", "lpv_impact"=>-0.8397},
-                            "1"=>{"variable"=>"Chemotherapy", "name"=>{"zh_tw"=>"化學治療", "en"=>"Chemotherapy"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["否", "是"], "en"=>["No", "Yes"]}, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>0, "map_values"=>"", "active_choice"=>2, "disable_condition"=>"", "lpv_impact"=>-0.4147},
-                            "2"=>{"variable"=>"Radiotherapy", "name"=>{"zh_tw"=>"放射治療", "en"=>"Radiotherapy"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["否", "是"], "en"=>["No", "Yes"]}, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>0, "map_values"=>"", "active_choice"=>2, "disable_condition"=>"", "lpv_impact"=>-0.3203},
-                            "3"=>{"variable"=>"Targeted_therapy", "name"=>{"zh_tw"=>"標靶治療", "en"=>"Targeted therapy"}, "is_num"=>0, "hint"=>{"zh_tw"=>"抗HER2治療", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["否", "是"], "en"=>["No", "Yes"]}, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>0, "map_values"=>"", "active_choice"=>2, "disable_condition"=>"HER2_status != 1", "lpv_impact"=>-0.4687}
+                            "0"=>{"variable"=>"sex_value", "name"=>{"zh_tw"=>"性別<br/>(Sex)", "en"=>"Sex"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["男", "女"], "en"=>["Male", "Female"]}, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "1"=>{"variable"=>"age", "name"=>{"zh_tw"=>"年齡<br/>(Age)", "en"=>"Age"}, "is_num"=>1, "hint"=>{"zh_tw"=>"從 20 歲(含)開始至 98 歲", "en"=>"Age must be between 20 and 98"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[20, 98], "right"=>0, "is_float"=>0, "revert_value"=>0, "map_values"=>[], "cancer_predict_mapping_file"=>BSON::ObjectId('5f8e60441d41c801f600011a'), "need_map_values"=>0},
+                            "2"=>{"variable"=>"calH", "name"=>{"zh_tw"=>"心臟鈣化分數<br/>(Heart Calcification score)", "en"=>"Heart Calcification score"}, "is_num"=>1, "hint"=>{"zh_tw"=>"請輸入0到5000的數字", "en"=>"Please enter a number between 0 and 5000"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "range"=>[0, 5000], "right"=>0, "is_float"=>1, "revert_value"=>0, "map_values"=>[], "cancer_predict_mapping_file"=>BSON::ObjectId('5f8e66c71d41c801f6000139'), "need_map_values"=>0},
+                            "3"=>{"variable"=>"calAH", "name"=>{"zh_tw"=>"升主動脈鈣化分數", "en"=>"Aorta ascendens Calcification score"}, "hint"=>{"zh_tw"=>"請輸入0到10000的數字", "en"=>"Please enter a number between 0 and 10000"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "is_num"=>1, "range"=>[0, 10000], "right"=>0, "is_float"=>1, "revert_value"=>0, "map_values"=>[], "cancer_predict_mapping_file"=>BSON::ObjectId('5f8e6ded1d41c801f600013d'), "need_map_values"=>0},
+                            "4"=>{"variable"=>"calDH", "name"=>{"zh_tw"=>"降主動脈鈣化分數", "en"=>"Aorta descendens Calcification score"}, "hint"=>{"zh_tw"=>"請輸 入0到10000的數字", "en"=>"Please enter a number between 0 and 10000"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "is_num"=>1, "range"=>[0, 10000], "right"=>0, "is_float"=>1, "revert_value"=>0, "map_values"=>[], "cancer_predict_mapping_file"=>BSON::ObjectId('5f8e6ded1d41c801f600013e'), "need_map_values"=>0},
+                            "5"=>{"variable"=>"fat", "name"=>{"zh_tw"=>"脂肪分數", "en"=>"Fat"}, "hint"=>{"zh_tw"=>"請輸入20到408的數字", "en"=>"Please enter a number between 20 and 408"}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[], "en"=>[]}, "is_num"=>1, "range"=>[20, 408], "right"=>0, "is_float"=>1, "revert_value"=>0, "map_values"=>[], "cancer_predict_mapping_file"=>BSON::ObjectId('5f8e6ded1d41c801f600013f'), "need_map_values"=>0},
+                            "6"=>{"variable"=>"N4", "name"=>{"zh_tw"=>"腫瘤", "en"=>"Neoplasia"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "7"=>{"variable"=>"N12", "name"=>{"zh_tw"=>"癡呆症", "en"=>"Dementias"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "8"=>{"variable"=>"N20", "name"=>{"zh_tw"=>"慢性肝炎", "en"=>" Chronic hepatitis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "9"=>{"variable"=>"N31", "name"=>{"zh_tw"=>"垂體侏儒症", "en"=>" Pituitary dwarfism"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>0, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "10"=>{"variable"=>"O6", "name"=>{"zh_tw"=>"慢性腎病", "en"=>" Chronic Kidney Disease"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "11"=>{"variable"=>"N34", "name"=>{"zh_tw"=>"克羅恩病和潰瘍性結腸炎", "en"=>"Crohn's disease and ulcerative colitis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "12"=>{"variable"=>"N14", "name"=>{"zh_tw"=>"帕金森氏", "en"=>"Parkinson's disease"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "13"=>{"variable"=>"N26", "name"=>{"zh_tw"=>"多發性硬化症", "en"=>"Multiple sclerosis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>[" 有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "14"=>{"variable"=>"O3", "name"=>{"zh_tw"=>"高血壓", "en"=>"Multiple sclerosis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "15"=>{"variable"=>"O20", "name"=>{"zh_tw"=>"嚴重精神疾病", "en"=>"Severe mental illness"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "16"=>{"variable"=>"O18", "name"=>{"zh_tw"=>"類風溼關節炎", "en"=>"Rheumatoid arthritis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "cancer_predict_mapping_file"=>"", "need_map_values"=>0},
+                            "17"=>{"variable"=>"O11", "name"=>{"zh_tw"=>"非出血性腦血管疾病", "en"=>"Non-Hemorrhagic Cerebrovascular Disease"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "18"=>{"variable"=>"N29", "name"=>{"zh_tw"=>"強直性脊柱炎", "en"=>"Ankylosing spondylitis"}, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "19"=>{"variable"=>"N6", "name"=>{"zh_tw"=>"動脈血管", "en"=>"Arterial vasculopathy"}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>""}, "comment_text"=>{"zh_tw"=>"", "en"=>""}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>["yes", "no"]}, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "20"=>{"variable"=>"O14", "name"=>{"zh_tw"=>"葡萄糖不耐症", "en"=>nil}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>nil}, "comment_text"=>{"zh_tw"=>"", "en"=>nil}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>nil}, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "21"=>{"variable"=>"N43", "name"=>{"zh_tw"=>"Basedow's disease", "en"=>nil}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>nil}, "comment_text"=>{"zh_tw"=>"", "en"=>nil}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>nil}, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "22"=>{"variable"=>"O17", "name"=>{"zh_tw"=>"偏頭痛", "en"=>nil}, "is_num"=>0, "hint"=>{"zh_tw"=>"", "en"=>nil}, "comment_text"=>{"zh_tw"=>"", "en"=>nil}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>nil}, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0},
+                            "23"=>{"variable"=>"O9", "name"=>{"zh_tw"=>"心臟衰竭", "en"=>nil}, "hint"=>{"zh_tw"=>"", "en"=>nil}, "comment_text"=>{"zh_tw"=>"", "en"=>nil}, "choice_fields"=>{"zh_tw"=>["有", "沒有"], "en"=>nil}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0}
                           }
+  field :form_show_in_result ,  :type=> Hash ,default: {}
   field :form_result_is_right , :type=> Integer ,default: 0
   field :text_descibe ,type:Hash ,default: {
-                            "zh_tw"=>"歡迎使用台灣準備乳癌預後系統！<br />\r\n本預測系統由台灣癌症登記資料庫2011至2015年間共20,997位乳癌病人所建立<br />\r\n並驗證美國流行病學癌症資料庫59,271位病人所建立 。<br />\r\n若要開始 請在下方選擇相關資訊",
-                            "en"=>"Welcome to the Taiwan Breast Cancer Prediction System!<br />\r\nThe prediction system is constructed using clinical data from 90,841 breast cancer patients in the Taiwan Cancer Registry database between 2011 to 2015, and validated using clinical data from 49,374 breast cancer patients in the U.S.-based Surveillance, Epidemiology and End Results (SEER) database.<br />\r\nTo start, please select the information below."
+                            "zh_tw"=>"歡迎使用台灣心血管 疾病預後預測系統<br />\r\n本預測系統由全民健保資料庫2017年~2020年間共1700位病人電腦斷層影像所建立之預測模型<br />\r\n請 在下方填入相關資訊",
+                            "en"=>"Welcome to the Taiwan cardiovascular disease prognosis prediction&nbsp;System!<br />\r\nThe prediction system is a prediction model established by CT images of 1,700 patients form the National Health Insurance Database&nbsp;between 2017 to 2020.<br />\r\nTo start, please select the information below."
                           }
   field :small ,type:Hash ,default:{'font_size'=>"0.825em",'active'=>0}
   field :medium ,type:Hash ,default:{'font_size'=>"1em",'active'=>1}
   field :large ,type:Hash ,default:{'font_size'=>"1.25em",'active'=>0}
-  field :head_images_id ,type:Array , default: [BSON::ObjectId('5df62cfc8cd8924e79000009'), BSON::ObjectId('5df745a58cd8924491000006'), BSON::ObjectId('5e7848c98cd8924f8d00004a'), BSON::ObjectId('5ea8f3e48cd892760b000011')]
-  field :title_images_id ,type:Array , default: [BSON::ObjectId('5df87cd88cd8924491000036')]
-  field :title_texts ,type:Hash ,default: {"zh_tw"=>"華人癌症存活預測", "en"=>"Asian breast cancer prediction"}
-  field :table_above_texts ,type:Hash ,default: {"zh_tw"=>"下表之分析為針對手術後病人，根據選定的術後治療，分別估計在第1年、3 及5年的存活率。", "en"=>"The analysis is for women who had undergone surgery.The table shows the 1-, 3- and 5-year survival rates,based on the treatment you have selected."}
-  field :text_above_texts ,type:Hash ,default: {"zh_tw"=>"此研究分析來自已接受根除性手術後之婦女所得之結果，根據您所輸入的資訊以及治療方式，在術後<br/>第{{years}}年，", "en"=>"The analysis is for women who had undergone surgery. Base on the information and the treatment you have selected, the predictions of survival status<br/>{{years}}"}
-  field :surgery_only_texts ,type:Hash ,default: {"zh_tw"=>"100 位只接受根除性手術的婦女中，有{{Surgery_only}}位婦女，術後{{surgery_year}}年仍為存活", "en"=>"after surgery are as follows:<br/>{{Surgery_only}} out of 100 women treated with surgery only are alive at {{surgery_year}} years."}
+  field :head_images_id ,type:Array , default: []
+  field :title_images_id ,type:Array , default: []
+  field :title_texts ,type:Hash ,default: {"zh_tw"=>"臺灣心血管疾病存活預測", "en"=>"Cardiovascular Disease Survival Forecast in Taiwan"}
+  field :table_above_texts ,type:Hash ,default: {"zh_tw"=>"下表之分析為針對手術後病人，根據選定的術後治療，分別估計在一年、一年半、兩年及兩年半的心血管疾病住院或死亡機率。", "en"=>"The analysis is for women who had undergone surgery.The table shows the 1,1.5, 2 and 2.5 year survival rates,based on the treatment you have selected."}
+  field :text_above_texts ,type:Hash ,default: {"zh_tw"=>"此研究分析來自於照射胸部電腦斷層所得之結果，根據您所輸入的資訊，在第{{years}}年內，有{{Surgery_only}}%的 機率可能心血管疾病住院或死亡。", "en"=>"This research comes from the results obtained by irradiating the chest CT. According to the information you entered that you have the {{Surgery_only}}% of hospitalization or death for cardiovascular disease within {{years}} years."}
+  field :surgery_only_texts ,type:Hash ,default: {"zh_tw"=>"", "en"=>""}
   field :extra_texts ,type:Hash ,default: {"zh_tw"=>"，此外", "en"=>""}
   field :extra_therapy_texts ,type:Hash ,default: {"zh_tw"=>"100 位在術後有接受{{extra_therapy}}的婦女中，有{{survival_num}}位婦女，術後{{surgery_year}}年仍為存活(多了{{Additional_Benefit}}位)", "en"=>"{{survival_num}} out of 100 women treated with {{extra_therapy}} are alive (an extra {{Additional_Benefit}})"}
   field :danger_texts ,type:Hash ,default: {"zh_tw"=>"請注意紅框的輸入資料是否符合要求!", "en"=>"Please check whether input data in red blocks are correct!"}
-  field :years ,type:Array ,default:[1,3,5]
+  field :years ,type:Array ,default:[1, 1.5, 2, 2.5]
   field :texts_between_Result_and_result_block ,type:Hash ,default: {"zh_tw"=>"如果欲將預測結果應用於臨床上，請務必與您的主治醫師討論後再做最後決定。", "en"=>"Please note that the patients need to consult with their medical doctors before making any decision."}
   #field :image_uploader ,type:Object
-  field :prediction_formula , type: String ,default: "lpv = ((age1-0.7276655)*(-10.87)+(age2+0.4540707)*8.968+(size1-0.643632)*0.7678+(nposit-1.346932)*0.5339+
-      grade_2*0.4795+grade_3*0.818+subtype_HER2*0.1806+subtype_triple*0.6457+pstage_2*0.5311+
-      pstage_3*1.134+pstage_4*2.172+lvi_yes*0.3321-0.04+chemo*(-0.4147)+radio*(-0.3203)+hormone*(-0.8397)+target*(0.3321)
-)"
-  field :years_settings , type: Array , default: ["exp(-0.001476145)^( exp(lpv) )","exp(-0.01261639)^( exp(lpv) )","exp(-0.02519608)^( exp(lpv) )"]
+  field :prediction_formula , type: String ,default: "A = 0.1327868* (sex_value- 0.4858824)
+
+       + 0.0371720* (age_test1 - 61.56000) -0.07447278* (age_test2 - 13.10152)
+
+       + 0.4315686* (age_test3 -  0.9844332)
+
+       + 0.0009163615*( calH_test1  - 182.9347)
+
+       -0.0007536899*( calH_test2 - 124.8706) -0.00004697183*( calH_test3  -80.75636)
+
+       + 0.0001401325*( calAH_test1  - 700.7824)
+
+       -0.001349783*( calAH_test2 - 634.2167) +0.001753832*( calAH_test3  -419.3361)
+
+       + 0.0001906046*( calDH_test1  -835.2894) -0.000251567*( calDH_test2 - 213.1630)
+
+       -0.002173942*( fat_test1  -108.4149)+0.003066541*( fat_test2 - 28.33497)
+
+       +0.6700708*(N4-0.3241176)
+
+       +0.3336162*(O3-0.4994118)
+
+       +0.1322476*(O20-0.1741176)
+
+       +0.9084972*(O18-0.008823529)
+
+       +0.2978388*(N12-0.1152941)
+
+       +0.1777935*(N20-0.3582353)
+
+       +1.588042*(N31-0.002352941)
+
+       +0.2197419*(O6-0.07823529)
+
+       +1.791159*(N34-0.001176471)
+
+       +0.4305973*(N14-0.02176471)
+
+       -0.4472885*(N29-0.02411765)
+
+       +0.2601319*(N26-0.04941176)
+
+       -0.2364269*(O11-0.1164706)
+
+       +0.1784179*(N6-0.1070588)
+
+       +0.6023170*(O14-0.01294118)
+
+       -1.031959*(N43-0.007058824)
+
+       +0.4257809*(O17-0.01823529)
+
+       +0.2002546*(O9-0.06176471)"
+  field :years_settings , type: Array , default: ["0.8095037^( exp(A) )", "0.729158^( exp(A) )", "0.6717211^( exp(A) )", "0.6056773^( exp(A) )"]
   field :tmp_years_settings , type: Array , default: []
   field :tmp_years_settings_for_ruby , type: Array , default: []
-  field :hidden_variables, type: String, default: "age1 = (age / 100.0) ^ (0.5)
-  age2 = age1 * log(age / 100.0)
-  size1 = log(size / 10.0)
-  ratio = (lymph_nodes_examined == 0 ? 0 : (1.0 * lymph_nodes_positive / lymph_nodes_examined))
-  ratio = (ratio > 1 ? 1 : ratio)
-  T4 = (tumor_direct_extension == 1)
-  T1 = !T4 && (size <= 20)
-  T2 = !T4 && !T1 && (size > 20 && size <= 50)
-  T = (T4 ? 'T4' : (T1 ? 'T1' : (T2 ? 'T2' : 'T3')))
-  N0 = (lymph_nodes_positive == 0)
-  N1_or_N1mi = !N0 && (lymph_nodes_positive >= 1 && lymph_nodes_positive <= 3)
-  N1 = N1_or_N1mi && micrometastasis != 1
-  N1mi = N1_or_N1mi && micrometastasis == 1
-  N2 = !N0 && !N1_or_N1mi && (lymph_nodes_positive <= 9)
-  N = (N0 ? 'N0' : (N1 ? 'N1' : (N1mi ? 'N1mi' : (N2 ? 'N2' : 'N3'))))
-  M = (Distant_Metastasis != 1) ? 'M0' : 'M1'
-  pstage = (M == 'M1' ? 4 : ((T == 'T1' && (N == 'N0' || N == 'N1mi')) ? 1 : (((T == 'T2' || T == 'T3') && (N == 'N0')) || ((T == 'T1' || T == 'T2') && (N == 'N1')) ? 2 : 3)) )
-  nposit = ((ratio + 0.1) / 0.1) ^ 0.5
-  grade_2 = (grade == 2 || grade == 4) ? 1 : 0
-  grade_3 = (grade == 3) ? 1 : 0
-  subtype_1 = (ER_status != 2 || PR_status != 2) && (HER2_status != 1)
-  subtype_2 = !subtype_1 && (HER2_status == 1)
-  subtype_3 = !subtype_1 && !subtype_2 && (ER_status == 2 && PR_status == 2 && HER2_status != 1)
-  subtype_HER2 = subtype_2 ? 1 : 0
-  subtype_triple = subtype_3 ? 1 : 0
-  pstage_2 = (pstage == 2) ? 1 : 0
-  pstage_3 = (pstage == 3) ? 1 : 0
-  pstage_4 = (pstage == 4) ? 1 : 0
-  lvi_yes = (lvi == 1) ? 1 : 0
-  chemo = (Chemotherapy == 2) ? 1 : 0
-  radio = (Radiotherapy == 2) ? 1 : 0
-  hormone = (hormone_therapy == 2) ? 1 : 0
-  target = (Targeted_therapy == 2) ? 1 : 0
-  "
+  field :hidden_variables, type: String, default: ""
   field :fix_hidden_variables, type: Array, default: []
   field :tmp_hidden_variables_for_ruby, type: String, default: ""
   field :tmp_hidden_variables_for_js, type: String, default: ""
@@ -189,8 +206,8 @@ class Cancerpredictfields
     tmp_table_translations = {}
     tmp_text_translations = {}
     @years = self.years
-    @head_name = ['Treatment','Additional_Benefit','Overall_Survival']
-    # @head_name = ['Treatment','Overall_Survival']
+    # @head_name = ['Treatment','Additional_Benefit','Overall_Survival']
+    @head_name = ['Treatment','Overall_Survival']
     @therapy_names = self.treatment_method
     I18n.available_locales.each do |locale|
       I18n.with_locale(locale) do
@@ -198,7 +215,7 @@ class Cancerpredictfields
         @therapy_choices = [I18n.t('cancerpredict.table.Surgeryonly')]
         self.form_show_in_result.values.each{|choice| @therapy_choices.push choice["name"][locale].to_s}
         tmp_table = "<span class=\"result_title print_only\">#{I18n.t("cancerpredict.table.table")}</span><div style=\"clear: both\"></div>"
-        tmp_table += '<input id="current_year" type="hidden" value="'+@years[-1].to_s+'" index="0"/><p id="cancer_table_texts">'+self.table_above_texts[locale].to_s+'</p>'
+        tmp_table += '<input id="current_year" type="hidden" value="'+@years[0].to_s+'" index="0"/><p id="cancer_table_texts">'+self.table_above_texts[locale].to_s+'</p>'
         tmp_table += ('<a style="display: inline-block;">'+(locale.to_s == 'zh_tw' ? '第' : '')+'</a><a style="display: inline-block;">')
         @years.each{|year| tmp_table += ('<button class="cancer_years cancer_table_btn  btn btn-default btn-sm">'+year.to_s+'</button>')}
         tmp_table += ('</a><a style="display: inline-block;">'+(locale == 'zh_tw' ? '年' : '')+'</a>')
@@ -293,7 +310,7 @@ class Cancerpredictfields
   end
   def reload_js_asset(path, force_reload=false)
     reload_any_asset(path, 'application/javascript', force_reload) do |new_path|
-      File.open(JSFileName, 'w+'){|f| f.write(new_path)}
+      File.open("#{Rails.root}/public/cancer_tool_js_filename.txt",'w+'){|f| f.write(new_path)}
     end
   end
   def generate_eval_formula
@@ -376,7 +393,7 @@ class Cancerpredictfields
       function calculate_and_change_result_value(obj){
         obj.servive_ratio_arr = [];
         for(var i = 0;i<obj.active_treatment.length;i++){
-          var servive_ratio = round(calculate_servive_ratio(obj.year,obj.lpv_real[i])*100,2);
+          var servive_ratio = round((1 - calculate_servive_ratio(obj.year,obj.lpv_real[i]))*100,2);
           var benefit = servive_ratio - obj.servive_ratio_arr[obj.servive_ratio_arr.length-1];
           obj.servive_ratio_arr.push(servive_ratio);
           $('tr.'+obj.active_treatment[i]+' td.Overall_Survival').html(servive_ratio+'%');
@@ -423,7 +440,8 @@ class Cancerpredictfields
   end
   def auto_write_predict_js(force_reload=true)
     js_codes = generate_jscode
-    save_path = "#{ModuleAppPath}/app/assets/javascripts/#{JS}"
+    module_app_path = Pathname.new(File.expand_path(__dir__)).dirname.dirname.to_s
+    save_path = module_app_path + '/app/assets/javascripts/cancer_predict.js'
     file_texts = File.read(save_path)
     need_write = false
     str1 = "/* auto add start */"
@@ -487,8 +505,8 @@ class Cancerpredictfields
     if need_write
       File.write(save_path,file_texts)
       reload_js_asset(save_path, force_reload)
-    elsif !(File.exist?(JSFileName))
-      File.open(JSFileName, 'w+'){|f| f.write(save_path)}
+    elsif !(File.exist?("#{Rails.root}/public/cancer_tool_js_filename.txt"))
+      File.open("#{Rails.root}/public/cancer_tool_js_filename.txt",'w+'){|f| f.write(save_path)}
     end
   end
   def get_years_settings_dict

app/views/admin/cancerpredicts/_form.html.erb

@@ -16,7 +16,6 @@
       <%else%>
         <% @disp_value = @value %>
       <%end%>
-      <% @disp_value = bc_yaml_dump(@disp_value) if value_type == 'Array' %>
       <% field_type = ((value_type == 'String' || value_type == 'Array' || value_type == 'Float') ? "text_field" : value_type) %>
       <% if value_type == 'Fixnum' %>
         <% if @value == 1%>

app/views/admin/cancerpredicts/index.html.erb

@@ -277,27 +277,15 @@
 		<div><%= form.check_box "form_result_is_right",{:checked=>false,:class=>"checkbox",:style=>"float: left;position: relative;left: 0;transform: none!important;margin-left: 1em;",:id=>"form_result_is_right"}%></div>
 	<%end%>
 	<div style="clear:both;"></div>
-	<% @create_items = ['years','table_above_texts','text_above_texts','surgery_only_texts','extra_texts','extra_therapy_texts','danger_texts','texts_between_Result_and_result_block']
-	   array_indices = [0]
-	%>
-	<% @create_items.each_with_index do |item, i|%>
+	<% @create_items = ['years','table_above_texts','text_above_texts','surgery_only_texts','extra_texts','extra_therapy_texts','danger_texts','texts_between_Result_and_result_block'] %>
+	<% @create_items.each do |item|%>
 		<label for="<%=item%>" style="float: left;margin-right:1em;width:11em;"><%= t('cancerpredict.'+item)+':' %></label>
 		<% if @form_to_show[item].class == BSON::Document || @form_to_show[item].class == Hash %>
 			<%= form.fields_for item do |locale_fields|%>
-				<% value = @form_to_show[item][I18n.locale.to_s]
-					 if array_indices.include?(i)
-						 value = bc_yaml_dump(value)
-					 end
-				%>
-				<%= locale_fields.text_field I18n.locale.to_s,{:value=> value,:id=> item,:style=>'width:calc(100% - 16em)'} %>
+				<%= locale_fields.text_field I18n.locale.to_s,{:value=>@form_to_show[item][I18n.locale.to_s] ,:id=> item,:style=>'width:calc(100% - 16em)'} %>
 			<% end %>
 		<% else %>
-				<% value = @form_to_show[item]
-					 if array_indices.include?(i)
-						 value = bc_yaml_dump(value)
-					 end
-				%>
-			<%= form.text_field item,{:value=> value,:id=> item,:style=>'width:calc(100% - 16em)'} %>
+			<%= form.text_field item,{:value=>@form_to_show[item],:id=> item,:style=>'width:calc(100% - 16em)'} %>
 		<% end %>
 		<div style="clear:both;"></div>
 	<% end %>

config/locales/en.yml

@@ -1,14 +1,14 @@
 en:
   module_name:
-    cancerpredict: Predict Breast Cancer Tool
+    cancerpredict: Cardiovascular Disease Survival Forecast in Taiwan Tool
   cancerpredict:
     hidden_variables: "Hidden Variables"
     advance_mode_hint1: "After opening advance mode，calculation will change!\nAre you sure switch to advance mode?"
     advance_mode_hint2: "一般模式: 選項設定在計算時對應到的值由1開始。(例如: 選項設定為[\"是\",\"否\"]，則\"是\"在計算時對應到1，而\"否\"在計算時對應到2)。<br><hr class=\"solid_line_hr\">進階模式: 選項設定在計算時對應到的值由0開始。<br>而若開啟選項值從大到小，則0對應到選項設定中的最後一項。<br>選項對應到的值的意思為當前述的計算值為0時，則對應到定義的Array的第1個元素的值，以此類推。<br>欄位對應檔案可上傳一個csv檔案，在計算時，會先依照csv中的第1直行，找到對應的變數1(生成的變數名稱為csv中的第1列)的值，其餘生成的變數值則為對應之後的同一橫列的值。"
     module_mode: Module Mode
     advance_mode: Advance Mode
-    Overall_Survival: Overall Survival
-    cancerpredict: Adjust the predict breast cancer tool
+    Overall_Survival: Probability
+    cancerpredict: Adjust Cardiovascular Disease Survival Forecast in Taiwan Tool
     submitResult: see submit results of the users
     result_is_right: Is therapy choices in the right hand side of result block?
     text_descibe: text descibe
@@ -33,7 +33,7 @@ en:
     texts_between_Result_and_result_block: Texts between "Result" and "Result block"
     prev_page: Previous page
     next_page: Next page
-    export_cancer_predict_tool_records: Export cancer predict tool records
+    export_cancer_predict_tool_records: Export Cardiovascular Disease Survival Forecast in Taiwan Tool records
     table:
         welcome: Welcome to The after breast cancer healing system of Taiwanprepare!\nTo start, please enter the relevant information below.
         Reset: Reset
@@ -52,10 +52,10 @@ en:
         no: no
         unknown: unknown
         Results: Results
-        Treatment: Treatment
+        Treatment: Event
         Additional_Benefit: 	Additional Benefit
-        Overall_Survival: Overall Survival(%)
-        Surgeryonly: Surgery only
+        Overall_Survival: Probability(%)
+        Surgeryonly: Readmission or death
         Hormonetherapy: Hormone therapy
         Chemotherapy: Chemotherapy
         years: years

config/locales/zh_tw.yml

@@ -1,14 +1,14 @@
 zh_tw:
   module_name:
-    cancerpredict: 乳癌預測工具
+    cancerpredict: 臺灣心血管疾病存活預測工具
   cancerpredict:
     hidden_variables: "隱藏的變數"
     advance_mode_hint1: "開啟進階模式後，計算方式有差異。\n您確定要開啟進階模式?"
     advance_mode_hint2: "一般模式: 選項設定在計算時對應到的值由1開始。(例如: 選項設定為[\"是\",\"否\"]，則\"是\"在計算時對應到1，而\"否\"在計算時對應到2)。<br><hr class=\"solid_line_hr\">進階模式: 選項設定在計算時對應到的值由0開始。<br>而若開啟選項值從大到小，則0對應到選項設定中的最後一項。<br>選項對應到的值的意思為當前述的計算值為0時，則對應到定義的Array的第1個元素的值，以此類推。<br>欄位對應檔案可上傳一個csv檔案，在計算時，會先依照csv中的第1直行，找到對應的變數1(生成的變數名稱為csv中的第1列)的值，其餘生成的變數值則為對應之後的同一橫列的值。"
     module_mode: 模組模式
     advance_mode: 進階模式
-    Overall_Survival: 總生存率
-    cancerpredict: 乳癌預測工具調整
+    Overall_Survival: Probability
+    cancerpredict: 臺灣心血管疾病存活預測工具調整
     submitResult: 查看用戶繳交表單結果
     result_is_right: 治療選項在結果的右邊?
     text_descibe: 文字說明
@@ -33,7 +33,7 @@ zh_tw:
     texts_between_Result_and_result_block: 在"結果"和"結果區塊"之間的文字
     prev_page: 上一頁
     next_page: 下一頁
-    export_cancer_predict_tool_records: 匯出乳癌預測系統的使用者紀錄
+    export_cancer_predict_tool_records: 匯出臺灣心血管疾病存活預測工具的使用者紀錄
     table:
         welcome: 歡迎使用台灣準備乳癌癒後系統！\n若要開始 請在下方輸入相關資訊
         Reset: 重置
@@ -52,9 +52,9 @@ zh_tw:
         no: 否
         unknown: 未知
         Results: 結果
-        Treatment: 治療
+        Treatment: Event(事件)
         Additional_Benefit: 額外治療效益
-        Overall_Survival: 總生存率(%)
+        Overall_Survival: Probability(機率)(%)
         Surgeryonly: 純手術
         Hormonetherapy: 賀爾蒙治療
         Chemotherapy: 化學治療

lib/cancerpredict/engine.rb

@@ -12,13 +12,12 @@ module Cancerpredict
         set_keyword_contstraints ['cancerpredictResult']
     		frontend_enabled
     		side_bar do
-          head_label_i18n 'cancerpredict.cancerpredict', icon_class: "icons-tools"
-          available_for "users"
-          active_for_controllers (['admin/cancerpredicts'])
-          head_link_path "admin_cancerpredicts_path"
-          set_sidebar_order -10
+              head_label_i18n 'cancerpredict.cancerpredict', icon_class: "icons-megaphone"
+              available_for "users"
+              active_for_controllers (['admin/cancerpredicts'])
+              head_link_path "admin_cancerpredicts_path"
 
-          context_link 'cancerpredict.cancerpredict',
+              context_link 'cancerpredict.cancerpredict',
                                     :link_path=>"admin_cancerpredicts_path" ,
                                     :priority=>1,
                                     :active_for_action=>{'admin/cancerpredicts'=>'index'},

modules/cancerpredict/info.json

@@ -3,8 +3,8 @@
 		{
 			"filename" : "cancer_predict_index",
 			"name" : {
-				"zh_tw" : "1. 乳癌預測工具",
-				"en" : "1. Breast cancer predict tool"
+				"zh_tw" : "1. 臺灣心血管疾病存活預測工具",
+				"en" : "1. Cardiovascular Disease Survival Forecast Tool"
 				},
 			"thumbnail" : "thumb.png"
 		}
@@ -13,8 +13,8 @@
 		{
 			"filename" : "cancer_predict_widget",
 			"name" : {
-				"zh_tw" : "1. 乳癌預測工具",
-				"en" : "1. Breast cancer predict tool"
+				"zh_tw" : "1. 臺灣心血管疾病存活預測工具",
+				"en" : "1. Cardiovascular Disease Survival Forecast Tool"
 				},
 			"thumbnail" : "thumb.png"
 		}