import os import sys import yaml import time import yaml import sys def check_config_file(task,config_file): with open(config_file) as f: config = yaml.safe_load(f) if task=='Phenotype': disease_label = config['disease_label'] else : disease_label = "" time = config['timePrediction'] label = task timeW = config['timeWindow'] include=int(timeW.split()[1]) bucket = config['timebucket'] radimp = config['radimp'] predW = config['predW'] disease_filter = config['disease_filter'] icu_no_icu = config['icu_no_icu'] groupingDiag = config['groupingDiag'] #assert( icu_no_icu in ['ICU','Non-ICU' ], "Chossen data should be one of the following: ICU, Non-ICU") assert( icu_no_icu =='ICU', "The dataset is only available for ICU data") data_icu = icu_no_icu=='ICU' if data_icu: chart_flag = config['chart'] output_flag = config['output'] select_chart = config['select_chart'] lab_flag = False select_lab = False else: lab_flag =config['lab'] select_lab = config['select_lab'] groupingMed = config['groupingMed'] groupingProc = config['groupingProc'] chart_flag = False output_flag = False select_chart = False diag_flag= config['diagnosis'] proc_flag = config['proc'] meds_flag = config['meds'] select_diag= config['select_diag'] select_med= config['select_med'] select_proc= config['select_proc'] select_out = config['select_out'] outlier_removal=config['outlier_removal'] thresh=config['outlier'] left_thresh=config['left_outlier'] if data_icu: assert (isinstance(select_diag,bool) and isinstance(select_med,bool) and isinstance(select_proc,bool) and isinstance(select_out,bool) and isinstance(select_chart,bool), " select_diag, select_chart, select_med, select_proc, select_out should be boolean") assert (isinstance(chart_flag,bool) and isinstance(output_flag,bool) and isinstance(diag_flag,bool) and isinstance(proc_flag,bool) and isinstance(meds_flag,bool), "chart_flag, output_flag, diag_flag, proc_flag, meds_flag should be boolean") else: assert (isinstance(select_diag,bool) and isinstance(select_med,bool) and isinstance(select_proc,bool) and isinstance(select_out,bool) and isinstance(select_lab,bool), " select_diag, select_lab, select_med, select_proc, select_out should be boolean") assert (isinstance(lab_flag,bool) and isinstance(diag_flag,bool) and isinstance(proc_flag,bool) and isinstance(meds_flag,bool), "lab_flag, diag_flag, proc_flag, meds_flag should be boolean") if task=='Phenotype': if disease_label=='Heart Failure': label='Readmission' time=30 disease_label='I50' elif disease_label=='CAD': label='Readmission' time=30 disease_label='I25' elif disease_label=='CKD': label='Readmission' time=30 disease_label='N18' elif disease_label=='COPD': label='Readmission' time=30 disease_label='J44' else : raise ValueError('Disease label not correct provide one in the list: Heart Failure, CAD, CKD, COPD') predW=0 assert (timeW[0]=='Last' and include<=72 and include>=24, "Time window should be between Last 24 and Last 72") elif task=='Mortality': time=0 label= 'Mortality' assert (predW<=8 and predW>=2, "Prediction window should be between 2 and 8") assert (timeW[0]=='Fisrt' and include<=72 and include>=24, "Time window should be between First 24 and First 72") elif task=='Length_of_Stay': label= 'Length of Stay' assert (timeW[0]=='Fisrt' and include<=72 and include>=24, "Time window should be between Fisrt 24 and Fisrt 72") assert (time<=10 and time>=1, "Length of stay should be between 1 and 10") predW=0 elif task=='Readmission': label= 'Readmission' assert (timeW[0]=='Last' and include<=72 and include>=24, "Time window should be between Last 24 and Last 72") assert (time<=150 and time>=10 and time%10==0, "Readmission window should be between 10 and 150 with a step of 10") predW=0 else: raise ValueError('Task not correct') assert( disease_filter in ['Heart Failure','COPD','CKD','CAD',""], "Disease filter should be one of the following: Heart Failure, COPD, CKD, CAD or empty") assert( groupingDiag in ['Convert ICD-9 to ICD-10 and group ICD-10 codes','Keep both ICD-9 and ICD-10 codes','Convert ICD-9 to ICD-10 codes'], "Grouping ICD should be one of the following: Convert ICD-9 to ICD-10 and group ICD-10 codes, Keep both ICD-9 and ICD-10 codes, Convert ICD-9 to ICD-10 codes") assert (bucket<=6 and bucket>=1 and isinstance(bucket, int), "Time bucket should be between 1 and 6 and an integer") assert (radimp in ['No Imputation', 'forward fill and mean','forward fill and median'], "imputation should be one of the following: No Imputation, forward fill and mean, forward fill and median") if chart_flag: assert (left_thresh>=0 and left_thresh<=10 and isinstance(left_thresh, int), "Left outlier threshold should be between 0 and 10 and an integer") assert (thresh>=90 and thresh<=99 and isinstance(thresh, int), "Outlier threshold should be between 90 and 99 and an integer") assert (outlier_removal in ['No outlier detection','Impute Outlier (default:98)','Remove outliers (default:98)'], "Outlier removal should be one of the following: No outlier detection, Impute Outlier (default:98), Remove outliers (default:98)") if lab_flag: assert (left_thresh>=0 and left_thresh<=10 and isinstance(left_thresh, int), "Left outlier threshold should be between 0 and 10 and an integer") assert (thresh>=90 and thresh<=99 and isinstance(thresh, int), "Outlier threshold should be between 90 and 99 and an integer") assert (outlier_removal in ['No outlier detection','Impute Outlier (default:98)','Remove outliers (default:98)'], "Outlier removal should be one of the following: No outlier detection, Impute Outlier (default:98), Remove outliers (default:98)") assert (groupingProc in ['ICD-9 and ICD-10','ICD-10'], "Grouping procedure should be one of the following: ICD-9 and ICD-10, ICD-10") assert (groupingMed in ['Yes','No'], "Do you want to group Medication codes to use Non propietary names? : Grouping medication should be one of the following: Yes, No") return label, time, disease_label, predW def create_cohort(task, mimic_path, config_path): sys.path.append('./preprocessing/day_intervals_preproc') sys.path.append('./utils') sys.path.append('./preprocessing/hosp_module_preproc') sys.path.append('./model') import day_intervals_cohort import feature_selection_icu import feature_selection_hosp import day_intervals_cohort_v22 import data_generation_icu_modify import data_generation_modify root_dir = os.path.dirname(os.path.abspath('UserInterface.ipynb')) config_path='./config/'+config_path with open(config_path) as f: config = yaml.safe_load(f) version_path = mimic_path+'/' print(version_path) version = mimic_path.split('/')[-1][0] start = time.time() #----------------------------------------------config---------------------------------------------------- label, tim, disease_label, predW = check_config_file(task,config_path) icu_no_icu = config['icu_no_icu'] timeW = config['timeWindow'] include=int(timeW.split()[1]) bucket = config['timebucket'] radimp = config['radimp'] diag_flag = config['diagnosis'] proc_flag= config['proc'] med_flag = config['meds'] disease_filter = config['disease_filter'] groupingDiag = config['groupingDiag'] select_diag= config['select_diag'] select_med= config['select_med'] select_proc= config['select_proc'] if icu_no_icu=='ICU': out_flag = config['output'] chart_flag = config['chart'] select_out= config['select_out'] select_chart= config['select_chart'] lab_flag = False select_lab = False else: lab_flag = config['lab'] groupingMed = config['groupingMed'] groupingProc = config['groupingProc'] select_lab= config['select_lab'] out_flag = False chart_flag = False select_out= False select_chart= False # ------------------------------------------------------------------------------------------------------------- data_icu=icu_no_icu=="ICU" data_mort=label=="Mortality" data_admn=label=='Readmission' data_los=label=='Length of Stay' if (disease_filter=="Heart Failure"): icd_code='I50' elif (disease_filter=="CKD"): icd_code='N18' elif (disease_filter=="COPD"): icd_code='J44' elif (disease_filter=="CAD"): icd_code='I25' else: icd_code='No Disease Filter' #-----------------------------------------------EXTRACT MIMIC----------------------------------------------------- if version == '2': cohort_output = day_intervals_cohort_v22.extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label) elif version == '1': cohort_output = day_intervals_cohort.extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label) #----------------------------------------------FEATURES------------------------------------------------------- if data_icu : feature_selection_icu.feature_icu(cohort_output, version_path,diag_flag,out_flag,chart_flag,proc_flag,med_flag) else: feature_selection_hosp.feature_nonicu(cohort_output, version_path,diag_flag,lab_flag,proc_flag,med_flag) #----------------------------------------------GROUPING------------------------------------------------------- group_diag=False group_med=False group_proc=False if data_icu: if diag_flag: group_diag=groupingDiag feature_selection_icu.preprocess_features_icu(cohort_output, diag_flag, group_diag,False,False,False,0,0) else: if diag_flag: group_diag=groupingDiag if med_flag: group_med=groupingMed if proc_flag: group_proc=groupingProc feature_selection_hosp.preprocess_features_hosp(cohort_output, diag_flag,proc_flag,med_flag,False,group_diag,group_med,group_proc,False,False,0,0) #----------------------------------------------SUMMARY------------------------------------------------------- if data_icu: feature_selection_icu.generate_summary_icu(diag_flag,proc_flag,med_flag,out_flag,chart_flag) else: feature_selection_hosp.generate_summary_hosp(diag_flag,proc_flag,med_flag,lab_flag) #----------------------------------------------FEATURE SELECTION--------------------------------------------- #----------------------------------------------FEATURE SELECTION--------------------------------------------- if data_icu: if select_chart or select_out or select_diag or select_med or select_proc: if select_chart: input('Please edit list of codes in ./data/summary/chart_features.csv to select the chart items to keep and press enter to continue') if select_out: input('Please edit list of codes in ./data/summary/out_features.csv to select the output items to keep and press enter to continue') if select_diag: input('Please edit list of codes in ./data/summary/diag_features.csv to select the diagnosis ids to keep and press enter to continue') if select_med: input('Please edit list of codes in ./data/summary/med_features.csv to select the meds items to keep and press enter to continue') if select_proc: input('Please edit list of codes in ./data/summary/proc_features.csv to select the procedures ids to keep and press enter to continue') feature_selection_icu.features_selection_icu(cohort_output, diag_flag,proc_flag,med_flag,out_flag, chart_flag,select_diag,select_med,select_proc,select_out,select_chart) else: if select_diag or select_med or select_proc or select_lab: if select_diag: input('Please edit list of codes in ./data/summary/diag_features.csv to select the diagnosis ids to keep and press enter to continue') if select_med: input('Please edit list of codes in ./data/summary/med_features.csv to select the meds items to keep and press enter to continue') if select_proc: input('Please edit list of codes in ./data/summary/proc_features.csv to select the procedures ids to keep and press enter to continue') if select_lab: input('Please edit list of codes in ./data/summary/labs_features.csv to select the labs items to keep and press enter to continue') feature_selection_hosp.features_selection_hosp(cohort_output, diag_flag,proc_flag,med_flag,lab_flag,select_diag,select_med,select_proc,select_lab) #---------------------------------------CLEANING OF FEATURES----------------------------------------------- thresh=0 if data_icu: if chart_flag: outlier_removal=config['outlier_removal'] clean_chart=outlier_removal!='No outlier detection' impute_outlier_chart=outlier_removal=='Impute Outlier (default:98)' thresh=config['outlier'] left_thresh=config['left_outlier'] feature_selection_icu.preprocess_features_icu(cohort_output, False, False,chart_flag,clean_chart,impute_outlier_chart,thresh,left_thresh) else: if lab_flag: outlier_removal=config['outlier_removal'] clean_chart=outlier_removal!='No outlier detection' impute_outlier_chart=outlier_removal=='Impute Outlier (default:98)' thresh=config['outlier'] left_thresh=config['left_outlier'] feature_selection_hosp.preprocess_features_hosp(cohort_output, False,False, False,lab_flag,False,False,False,clean_chart,impute_outlier_chart,thresh,left_thresh) # ---------------------------------------time-Series Representation-------------------------------------------- if radimp == 'forward fill and mean' : impute='Mean' elif radimp =='forward fill and median': impute = 'Median' else : impute = False if data_icu: gen=data_generation_icu_modify.Generator(task,cohort_output,data_mort,data_admn,data_los,diag_flag,proc_flag,out_flag,chart_flag,med_flag,impute,include,bucket,predW) else: gen=data_generation_modify.Generator(cohort_output,data_mort,data_admn,data_los,diag_flag,lab_flag,proc_flag,med_flag,impute,include,bucket,predW) end = time.time() print("Time elapsed : ", round((end - start)/60,2),"mins") print("[============TASK COHORT SUCCESSFULLY CREATED============]")