import csv import json import os import pandas as pd import datasets import sys import pickle import subprocess import shutil from urllib.request import urlretrieve _DESCRIPTION = """\ Dataset for mimic4 data, by default for the Mortality task. Available tasks are: Mortality, Length of Stay, Readmission, Phenotype. The data is extracted from the mimic4 database using this pipeline: 'https://github.com/healthylaife/MIMIC-IV-Data-Pipeline/tree/main' mimic path should have this form : "absolute/path/to/mimic4data/mimiciv/2.2" """ _HOMEPAGE = "https://huggingface.co/datasets/thbndi/Mimic4Dataset" _CITATION = "https://proceedings.mlr.press/v193/gupta22a.html" _URL = "https://github.com/healthylaife/MIMIC-IV-Data-Pipeline" _DATA_GEN = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/data_generation_icu_modify.py' _DAY_INT= 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/day_intervals_cohort_v22.py' _COHORT = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/cohort.py' _CONFIG_URLS = {'los' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/los.config', 'mortality' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/los.config', 'phenotype' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/phenotype.config', 'readmission' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/readmission.config' } class Mimic4DatasetConfig(datasets.BuilderConfig): """BuilderConfig for Mimic4Dataset.""" def __init__( self, **kwargs, ): super().__init__(**kwargs) class Mimic4Dataset(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") def __init__(self, **kwargs): self.mimic_path = kwargs.pop("mimic_path", None) if self.mimic_path is None: raise ValueError("You must specify the path of the mimic4 data") if not os.path.exists(self.mimic_path): raise ValueError("The path of the mimic4 data does not exist") self.config_path = kwargs.pop("config_path",None) super().__init__(**kwargs) BUILDER_CONFIGS = [ Mimic4DatasetConfig( name="Phenotype", version=VERSION, description="Dataset for mimic4 Phenotype task" ), Mimic4DatasetConfig( name="Readmission", version=VERSION, description="Dataset for mimic4 Readmission task" ), Mimic4DatasetConfig( name="Length of Stay", version=VERSION, description="Dataset for mimic4 Length of Stay task" ), Mimic4DatasetConfig( name="Mortality", version=VERSION, description="Dataset for mimic4 Mortality task" ), ] DEFAULT_CONFIG_NAME = "Mortality" def _info(self): features = datasets.Features( { "label": datasets.ClassLabel(names=["0", "1"]), "gender": datasets.Value("string"), "ethnicity": datasets.Value("string"), "age": datasets.Value("int32"), "COND": datasets.Sequence(datasets.Value("string")), "MEDS": { "signal": { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) } , "rate": { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) } , "amount": { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) } }, "PROC": { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) }, "CHART": { "signal" : { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) }, "val" : { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) }, }, "OUT": { "id": datasets.Sequence(datasets.Value("int32")), "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))) }, } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, citation=_CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager()): if self.config.name == 'Phenotype' and self.config_path is None : self.config_path = _CONFIG_URLS['phenotype'] if self.config.name == 'Readmission' and self.config_path is None : self.config_path = _CONFIG_URLS['readmission'] if self.config.name == 'Length of Stay' and self.config_path is None : self.config_path = _CONFIG_URLS['los'] if self.config.name == 'Mortality' and self.config_path is None : self.config_path = _CONFIG_URLS['mortality'] #clone git repo if doesnt exists repo_url='https://github.com/healthylaife/MIMIC-IV-Data-Pipeline' if os.path.exists('MIMIC-IV-Data-Pipeline-main'): path_bench = os.path.dirname(os.path.abspath('MIMIC-IV-Data-Pipeline-main'))+'/MIMIC-IV-Data-Pipeline-main' else: repodir = os.getcwd() path_bench = repodir+'/MIMIC-IV-Data-Pipeline-main' subprocess.run(["git", "clone", repo_url, path_bench]) #download config file if not custom if self.config_path[0:4] == 'http': c = self.config_path.split('/')[-1] file_path, head = urlretrieve(self.config_path,c) else : file_path = self.config_path #create config folder if not os.path.exists(path_bench+'/config'): os.makedirs(path_bench+'/config') #save config file in config folder conf=path_bench+'/config/'+file_path.split('/')[-1] if not os.path.exists(conf): shutil.move(file_path, path_bench+'/config') #downloads modules from hub if not os.path.exists(path_bench+'/model/data_generation_icu_modify.py'): file_path, head = urlretrieve(_DATA_GEN, "data_generation_icu_modify.py") shutil.move(file_path, path_bench+'/model') if not os.path.exists(path_bench+'/preprocessing/day_intervals_preproc/day_intervals_cohort_v22.py'): file_path, head = urlretrieve(_DAY_INT, "day_intervals_cohort_v22.py") shutil.move(file_path, path_bench+'/preprocessing/day_intervals_preproc') if not os.path.exists(path_bench+'/cohort.py'): file_path, head = urlretrieve(_COHORT, "cohort.py") shutil.move(file_path, path_bench) data_dir = path_bench + "/data/dataDic" sys.path.append(path_bench) config = self.config_path.split('/')[-1] os.chdir(path_bench) script = 'python cohort.py '+ self.config.name +" "+ self.mimic_path+ " "+path_bench+ " "+config os.system(script) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir}), ] def _generate_examples(self, filepath): with open(filepath, 'rb') as fp: dataDic = pickle.load(fp) for hid, data in dataDic.items(): proc_features = data['Proc'] chart_features = data['Chart'] meds_features = data['Med'] out_features = data['Out'] cond_features = data['Cond']['fids'] eth= data['ethnicity'] age = data['age'] gender = data['gender'] label = data['label'] items = list(proc_features.keys()) values =[proc_features[i] for i in items ] procs = {"id" : items, "value": values} items_outs = list(out_features.keys()) values_outs =[out_features[i] for i in items_outs ] outs = {"id" : items_outs, "value": values_outs} #chart signal if ('signal' in chart_features): items_chart_sig = list(chart_features['signal'].keys()) values_chart_sig =[chart_features['signal'][i] for i in items_chart_sig ] chart_sig = {"id" : items_chart_sig, "value": values_chart_sig} else: chart_sig = {"id" : [], "value": []} #chart val if ('val' in chart_features): items_chart_val = list(chart_features['val'].keys()) values_chart_val =[chart_features['val'][i] for i in items_chart_val ] chart_val = {"id" : items_chart_val, "value": values_chart_val} else: chart_val = {"id" : [], "value": []} charts = {"signal" : chart_sig, "val" : chart_val} #meds signal if ('signal' in meds_features): items_meds_sig = list(meds_features['signal'].keys()) values_meds_sig =[meds_features['signal'][i] for i in items_meds_sig ] meds_sig = {"id" : items_meds_sig, "value": values_meds_sig} else: meds_sig = {"id" : [], "value": []} #meds rate if ('rate' in meds_features): items_meds_rate = list(meds_features['rate'].keys()) values_meds_rate =[meds_features['rate'][i] for i in items_meds_rate ] meds_rate = {"id" : items_meds_rate, "value": values_meds_rate} else: meds_rate = {"id" : [], "value": []} #meds amount if ('amount' in meds_features): items_meds_amount = list(meds_features['amount'].keys()) values_meds_amount =[meds_features['amount'][i] for i in items_meds_amount ] meds_amount = {"id" : items_meds_amount, "value": values_meds_amount} else: meds_amount = {"id" : [], "value": []} meds = {"signal" : meds_sig, "rate" : meds_rate, "amount" : meds_amount} yield int(hid), { "label" : label, "gender" : gender, "ethnicity" : eth, "age" : age, "COND" : cond_features, "PROC" : procs, "CHART" : charts, "OUT" : outs, "MEDS" : meds }