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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============]")
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