Compare commits

..

76 Commits

Author SHA1 Message Date
邱博亞 5acc13d76d Update sidebar order. 2024-08-23 23:14:34 +08:00
邱博亞 0fdbf08f9e Refine constant variables. 2024-08-23 22:47:20 +08:00
邱博亞 be5b892aee Format files. (fix indent) 2024-08-23 21:08:20 +08:00
邱博亞 d2b3464359 Refine constant variables. 2024-08-23 21:04:57 +08:00
邱博亞 64626817e9 Fix bug in backend setting. 2024-08-22 22:41:33 +08:00
邱博亞 2cb22f4f6f Fix bug. 2024-03-18 21:31:15 +08:00
邱博亞 e03e27dc17 remove carrierwave/processing/mime_type for new version 2024-03-18 21:22:36 +08:00
BoHung Chiu 93ef387b68 Fix js not reload bug. 2022-06-17 21:27:04 +08:00
BoHung Chiu f8264413f0 Fix bug. 2022-05-23 18:37:59 +08:00
BoHung Chiu 586f83142d Fix bug. 2022-05-23 18:21:24 +08:00
BoHung Chiu 5ffa34b151 Fix js bug. 2022-02-25 10:56:33 +08:00
BoHung Chiu dbbe675584 Fix js bug. 2022-02-25 10:48:47 +08:00
BoHung Chiu 2f7135e146 Fix bug. 2022-02-09 16:03:25 +08:00
BoHung Chiu 19daac4173 Fix css. 2022-02-09 15:37:00 +08:00
BoHung Chiu 5206181fed Fix bug. 2022-02-08 15:43:57 +08:00
BoHung Chiu 0ebff5a9e5 Fix bug. 2022-02-07 19:23:59 +08:00
BoHung Chiu 543b5cf42f Fix bug. 2022-02-07 19:16:57 +08:00
BoHung Chiu ca4a48cb51 Fix bug. 2022-02-07 18:30:10 +08:00
BoHung Chiu 40d4b889fd Fix bug. 2022-02-07 17:28:23 +08:00
BoHung Chiu 163805f8c1 Fix bug. 2022-01-28 15:52:07 +08:00
BoHung Chiu f897f12ef5 Fix bug. 2022-01-28 15:50:46 +08:00
BoHung Chiu e3c123e5aa Fix bug. 2022-01-28 15:40:23 +08:00
BoHung Chiu dd52046c16 Fix backend page bug. 2022-01-28 12:49:19 +08:00
BoHung Chiu 5bf740d454 Fix bug. 2022-01-27 17:04:13 +08:00
BoHung Chiu 742adb814d Fix bug. 2022-01-26 19:57:55 +08:00
BoHung Chiu 7724fd5769 Fix bug. 2022-01-26 19:49:52 +08:00
BoHung Chiu ca5c47d7f5 Fix bug. 2022-01-26 19:41:50 +08:00
BoHung Chiu 6a1cac01aa Fix bug. 2022-01-26 19:26:56 +08:00
BoHung Chiu 4b4c960d14 Fix bug. 2022-01-26 16:27:55 +08:00
BoHung Chiu 137e13ad1b Finish version 2.(lpv calculation is editable) 2022-01-26 14:05:57 +08:00
BOHUNG 9f3f337dec fix 2020-03-28 11:42:16 +08:00
BOHUNG 846024ac51 fix 2020-03-28 11:35:01 +08:00
BOHUNG f93a11d638 fix bugs(choose float field will get no value) in version 1. 2020-03-04 12:07:05 +08:00
BOHUNG 9428475124 add module_name to fix translations missing. 2020-02-24 15:31:28 +08:00
BOHUNG e116f69577 fix bug 2020-02-06 15:50:25 +08:00
BOHUNG db59135626 add export record feature 2020-02-03 16:47:49 +08:00
BOHUNG 817ecf0377 fix 2020-02-03 15:27:29 +08:00
BOHUNG 38e35fb560 fix problem in 2020/1/15 2020-01-28 18:24:52 +08:00
BOHUNG da1eed7786 fix 2020-01-13 19:19:11 +08:00
BOHUNG 19b2afcab1 fix 2020-01-13 19:16:41 +08:00
BOHUNG 65b96b9fdc fix 2020-01-13 19:15:43 +08:00
BOHUNG 25e3ae7fde add change bootstrap.js by code 2020-01-13 19:13:37 +08:00
BOHUNG 4620557e72 fix 2020-01-13 19:06:28 +08:00
BOHUNG cf9bec7a61 add auto copy index.erb to module 2020-01-13 19:04:02 +08:00
BOHUNG 893fe1e33b fix 2020-01-13 18:57:23 +08:00
BOHUNG 8f7a0ce704 add routed edit code 2020-01-13 18:54:51 +08:00
BOHUNG 52a197a68d fix some bug in js 2020-01-13 16:15:21 +08:00
BOHUNG 5962eed8a0 fix wrong layout in english 2020-01-13 15:38:21 +08:00
BOHUNG 9aba9a3f0b edit page css to fix the layout 2020-01-12 21:47:55 +08:00
BOHUNG 456ce12222 fix very much problems.
Let user change the texts in table and text tab.
Add the english contents.
fix print problem.
change contents before 2020/1/12
2020-01-12 13:14:58 +08:00
BOHUNG 4b8fed7e52 remove unused \ in the url 2019-12-28 18:54:28 +08:00
BOHUNG 77e92b7297 finish everything before 2019/12/26 2019-12-28 17:57:13 +08:00
BOHUNG 0101f3bef0 adjust some things about predict tools. 2019-12-27 13:49:20 +08:00
BOHUNG e2bc83ec2e finish edit content of tools before 2019/12/21(include the user choices) 2019-12-21 23:50:17 +08:00
BOHUNG 74fff06818 edit the calculate of the predict and edit css to make the logo in the right place and right size 2019-12-17 21:27:11 +08:00
BOHUNG 190752a275 finish the first version of predict tool.and finish the backend control panel of this tool. 2019-12-15 21:08:41 +08:00
BOHUNG 24d14e2b3b -0.5=>0.5,add image uploader 2019-12-14 12:21:09 +08:00
BOHUNG 788f495c29 After user submit,user can change input data,to see the result change. 2019-12-13 16:54:46 +08:00
chiu 7982622ca8 add the feature that will collect user input and user can edit the form in the admin page. 2019-12-11 23:59:17 +08:00
BOHUNG 1e41d84353 fix all problem 2019-12-10 19:33:28 +08:00
chiu f5af46731e fix bugs 2019-12-09 21:25:59 +08:00
BOHUNG 63bfb834ac vrsion 1 2019-12-09 09:47:53 +08:00
BOHUNG 98738db5d1 finish js 2019-12-09 00:43:40 +08:00
BOHUNG 8945e3b64a fix js bug 2019-12-09 00:38:40 +08:00
BOHUNG 32bd2ffac5 add calculate additional benefit and finish text result 2019-12-08 20:21:32 +08:00
BOHUNG 2e00a82db4 finish add overall_servival 2019-12-08 13:32:03 +08:00
BOHUNG 6b1d72e54a finish table and text except calculate 2019-12-07 21:01:52 +08:00
BOHUNG c1a2927e1e finish result choices and result_tab 2019-12-07 12:12:33 +08:00
BOHUNG d8d02fb590 finish the table and add the post of submit_btn and return the lpv result 2019-12-03 21:17:09 +08:00
BOHUNG 296e19929c add left and right block 2019-11-28 22:58:03 +08:00
BOHUNG 3353d1595b add create the cancer_predict_tool_table 2019-11-27 21:24:09 +08:00
BOHUNG be9c1f3d05 finish a half of predict_tool 2019-11-23 17:49:18 +08:00
BOHUNG 741d440631 add a lot of things 2019-11-23 16:14:56 +08:00
BOHUNG 88b5a9bbed add admin_index and set form_show 2019-11-23 11:15:11 +08:00
chiu d9be851646 Update cancerpredictfields.rb 2019-11-21 20:44:39 +08:00
chiu d4afee639d Update cancerpredictfields.rb 2019-11-21 20:36:20 +08:00
11 changed files with 1109 additions and 1147 deletions

View File

@ -327,6 +327,20 @@ $(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{
@ -338,7 +352,7 @@ $(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(0).addClass('active');
$('#result_table_content .cancer_years').eq(-1).addClass('active');
for(var i = 0;i < $('#result_table_content .cancer_years').length;i++){
$('#result_table_content .cancer_years').eq(i).attr('index',i)
};
@ -354,7 +368,7 @@ $(document).ready(function(){
});
load_heml = $('#result_text_content').html(result.responseJSON.texts);
load_heml.ready(function(){
$('#result_text_content .cancer_years').eq(0).addClass('active');
$('#result_text_content .cancer_years').eq(-1).addClass('active');
for(var i = 0;i < $('#result_text_content .cancer_years').length;i++){
$('#result_text_content .cancer_years').eq(i).attr('index',i)
};
@ -391,9 +405,9 @@ $(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];/*therapy_lpv end*/;
var lpv = /*therapy_lpv start*/[0, -0.8397, -0.4147, -0.3203, -0.4687];/*therapy_lpv end*/;
var lpv_dict={};
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*/
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*/
active_treatment.push = function() {
if(arguments.length == 1){
var year = $('#current_year').attr('value');
@ -402,7 +416,7 @@ $(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((1 - eval(lpv_calc[year]))*100,2);
var servive_ratio = round(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+'%');
@ -447,7 +461,7 @@ $(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((1 - eval(lpv_calc[year]))*100,2);
var servive_ratio = round(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+'%');
@ -603,135 +617,75 @@ $(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']);
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']));
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']);
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{
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)
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)
)
}catch(e){console.log(e)};
result['lpv_variable'] = {};
result['lpv_variable']['A'] = A;
result['lpv'] = A;
result['lpv_variable']['lpv'] = lpv;
result['lpv'] = lpv;
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((1 - calculate_servive_ratio(obj.year,obj.lpv_real[i]))*100,2);
var servive_ratio = round(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+'%');
@ -746,19 +700,16 @@ $(document).ready(function(){
function calculate_servive_ratio(year,obj){
var servive_ratio;
var A = obj['A'];
var lpv = obj['lpv'];
switch(year) {
case '1':
servive_ratio = 0.8095037**( Math.exp(A) );
servive_ratio = Math.exp(-0.001476145)**( Math.exp(lpv) );
break;
case '1.5':
servive_ratio = 0.729158**( Math.exp(A) );
case '3':
servive_ratio = Math.exp(-0.01261639)**( Math.exp(lpv) );
break;
case '2':
servive_ratio = 0.6717211**( Math.exp(A) );
break;
case '2.5':
servive_ratio = 0.6056773**( Math.exp(A) );
case '5':
servive_ratio = Math.exp(-0.02519608)**( Math.exp(lpv) );
break;
default:
console.log('not found year.');

File diff suppressed because it is too large Load Diff

View File

@ -1,221 +1,227 @@
# 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.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
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
end
def index
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$/)
asset = Rails.application.assets[js_filename]
preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
else
preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
end
end
{
"cancerpredict" => [],
"extras"=>{"table"=> @table_str,'preidct_js_url'=>preidct_js_url}
}
uid = OrbitHelper.params[:uid] rescue ""
tags = OrbitHelper.widget_tags
categories = OrbitHelper.widget_categories || []
@table_str = File.read(Cancerpredictfields::ToolTableMap[I18n.locale])
preidct_js_url = "/assets/#{Cancerpredictfields::JS}"
if File.exist?(Cancerpredictfields::JSFileName)
js_filename = File.read(Cancerpredictfields::JSFileName)
if js_filename.include?(Cancerpredictfields::JS)
asset = Rails.application.assets[js_filename]
preidct_js_url = "#{Rails.application.config.assets.prefix}/#{asset.digest_path}"
else
preidct_js_url = "#{Rails.application.config.assets.prefix}/#{File.basename(js_filename)}"
end
end
{
"cancerpredict" => [],
"extras" => { "table" => @table_str, "preidct_js_url" => preidct_js_url },
}
end
def widget
uid = OrbitHelper.params[:uid] rescue ""
tags = OrbitHelper.widget_tags
categories = OrbitHelper.widget_categories || []
@table_str = File.read('public/cancer_tool_table_tmp_'+I18n.locale.to_s+'.txt')
preidct_js_url = '/assets/cancer_predict.js'
if File.exist?('public/cancer_tool_js_filename.txt')
js_filename = File.read('public/cancer_tool_js_filename.txt')
if js_filename.match(/cancer_predict\.js$/)
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}
}
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 },
}
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
end

View File

@ -1,4 +1,13 @@
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

View File

@ -9,112 +9,95 @@ 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: true
field :advance_mode, type: Boolean, default: false
field :form_show , :type=> Hash ,default:{
"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"=>["", ""], "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "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"=>["", "沒有"], "en"=>nil}, "is_num"=>0, "range"=>[], "right"=>1, "is_float"=>0, "revert_value"=>1, "map_values"=>[], "need_map_values"=>0}
"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"=>["", "", "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"=>["", "", "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"=>["", "", "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"=>["", "", "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"=>["", ""], "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"=>["", ""], "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"=>["", ""], "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"=>["", ""], "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}
}
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."
"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."
}
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: []
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 :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 :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, 1.5, 2, 2.5]
field :years ,type:Array ,default:[1,3,5]
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: "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 :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 :tmp_years_settings , type: Array , default: []
field :tmp_years_settings_for_ruby , type: Array , default: []
field :hidden_variables, type: String, 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 :fix_hidden_variables, type: Array, default: []
field :tmp_hidden_variables_for_ruby, type: String, default: ""
field :tmp_hidden_variables_for_js, type: String, default: ""
@ -206,8 +189,8 @@ 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
@ -215,7 +198,7 @@ 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[0].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[-1].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>')
@ -310,7 +293,7 @@ class Cancerpredictfields
end
def reload_js_asset(path, force_reload=false)
reload_any_asset(path, 'application/javascript', force_reload) do |new_path|
File.open("#{Rails.root}/public/cancer_tool_js_filename.txt",'w+'){|f| f.write(new_path)}
File.open(JSFileName, 'w+'){|f| f.write(new_path)}
end
end
def generate_eval_formula
@ -393,7 +376,7 @@ 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((1 - calculate_servive_ratio(obj.year,obj.lpv_real[i]))*100,2);
var servive_ratio = round(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+'%');
@ -440,8 +423,7 @@ class Cancerpredictfields
end
def auto_write_predict_js(force_reload=true)
js_codes = generate_jscode
module_app_path = Pathname.new(File.expand_path(__dir__)).dirname.dirname.to_s
save_path = module_app_path + '/app/assets/javascripts/cancer_predict.js'
save_path = "#{ModuleAppPath}/app/assets/javascripts/#{JS}"
file_texts = File.read(save_path)
need_write = false
str1 = "/* auto add start */"
@ -505,8 +487,8 @@ class Cancerpredictfields
if need_write
File.write(save_path,file_texts)
reload_js_asset(save_path, force_reload)
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)}
elsif !(File.exist?(JSFileName))
File.open(JSFileName, 'w+'){|f| f.write(save_path)}
end
end
def get_years_settings_dict

View File

@ -16,6 +16,7 @@
<%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%>

View File

@ -277,15 +277,27 @@
<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'] %>
<% @create_items.each do |item|%>
<% @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|%>
<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|%>
<%= locale_fields.text_field I18n.locale.to_s,{:value=>@form_to_show[item][I18n.locale.to_s] ,:id=> item,:style=>'width:calc(100% - 16em)'} %>
<% 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)'} %>
<% end %>
<% else %>
<%= form.text_field item,{:value=>@form_to_show[item],:id=> item,:style=>'width:calc(100% - 16em)'} %>
<% 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)'} %>
<% end %>
<div style="clear:both;"></div>
<% end %>

View File

@ -1,14 +1,14 @@
en:
module_name:
cancerpredict: Cardiovascular Disease Survival Forecast in Taiwan Tool
cancerpredict: Predict Breast Cancer Tool
cancerpredict:
hidden_variables: "Hidden Variables"
advance_mode_hint1: "After opening advance modecalculation 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: Probability
cancerpredict: Adjust Cardiovascular Disease Survival Forecast in Taiwan Tool
Overall_Survival: Overall Survival
cancerpredict: Adjust the predict breast cancer 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 Cardiovascular Disease Survival Forecast in Taiwan Tool records
export_cancer_predict_tool_records: Export cancer predict 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: Event
Treatment: Treatment
Additional_Benefit: Additional Benefit
Overall_Survival: Probability(%)
Surgeryonly: Readmission or death
Overall_Survival: Overall Survival(%)
Surgeryonly: Surgery only
Hormonetherapy: Hormone therapy
Chemotherapy: Chemotherapy
years: years

View File

@ -1,14 +1,14 @@
zh_tw:
module_name:
cancerpredict: 臺灣心血管疾病存活預測工具
cancerpredict: 乳癌預測工具
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: Probability
cancerpredict: 臺灣心血管疾病存活預測工具調整
Overall_Survival: 總生存率
cancerpredict: 乳癌預測工具調整
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: 匯出臺灣心血管疾病存活預測工具的使用者紀錄
export_cancer_predict_tool_records: 匯出乳癌預測系統的使用者紀錄
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:
unknown: 未知
Results: 結果
Treatment: Event(事件)
Treatment: 治療
Additional_Benefit: 額外治療效益
Overall_Survival: Probability(機率)(%)
Overall_Survival: 總生存率(%)
Surgeryonly: 純手術
Hormonetherapy: 賀爾蒙治療
Chemotherapy: 化學治療

View File

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

View File

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