thbndi commited on
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9dec6dd
1 Parent(s): 5ff6ba1

Update Mimic4Dataset.py

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Files changed (1) hide show
  1. Mimic4Dataset.py +4 -52
Mimic4Dataset.py CHANGED
@@ -10,7 +10,7 @@ from sklearn.model_selection import train_test_split
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  from sklearn.preprocessing import LabelEncoder
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  import yaml
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  import numpy as np
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- from .dataset_utils import vocab, concat_data, generate_deep, generate_ml
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  from .task_cohort import create_cohort
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@@ -532,61 +532,13 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
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  items= pd.read_csv(self.mimic_path+'/icu/d_items.csv.gz',compression='gzip', header=0)
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  with open(filepath, 'rb') as fp:
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  dico = pickle.load(fp)
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- for key, data in dico.items():
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-
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- #Diagnosis
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- if self.feat_cond:
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- conds = data['Cond']['fids']
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- cond_text=[]
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- for code in conds:
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- desc = icd[icd['code']==code]
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- if not desc.empty:
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- cond_text.append(desc['description'].to_string(index=False))
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- template = 'The patient is diagnosed with {}.'
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- cond_text = template.format(';'.join(cond_text))
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- else :
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- cond_text=''
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-
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- #chart
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- if self.feat_chart:
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- chart = data['Chart']
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- if chart:
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- charts=chart['val']
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- feat=charts.keys()
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- chart_val=[charts[key] for key in feat]
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- chart_mean = [round(np.mean(c),3) for c in chart_val]
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- feat_text = [(items[items['itemid']==f]['label']).to_string(index=False) for f in feat]
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- template='{} for {}'
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- chart_text = []
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- for mean_val, feat_label in zip(chart_mean, feat_text):
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- text = template.format(mean_val,feat_label)
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- chart_text.append(text)
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- chart_text='The chart events mesured are :{}.' + ';'.join(chart_text)
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- else:
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- chart_text=''
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-
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- #meds
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- if self.feat_meds:
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- meds = data['Med']
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- if meds:
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- meds=meds['val']
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- feat=meds['signal'].keys()
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- meds_val=[meds[key] for key in feat]
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- meds_mean = [round(np.mean(c),3) for c in meds_val]
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- feat_text = [(items[items['itemid']==f]['label']).to_string(index=False) for f in feat]
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- template='{} of {}'
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- meds_text = []
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- for mean_val, feat_label in zip(meds_mean, feat_text):
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- text = template.format(mean_val,feat_label)
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- meds_text.append(text)
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- meds_text='The medications administered are :{}.' + ';'.join(meds_text)
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- else:
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- meds_text=''
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  yield int(key),{
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  'label' : data['label'],
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- 'text': cond_text+chart_text+meds_text
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  }
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  #############################################################################################################################
 
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  from sklearn.preprocessing import LabelEncoder
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  import yaml
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  import numpy as np
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+ from .dataset_utils import vocab, concat_data, generate_deep, generate_ml, generate_text
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  from .task_cohort import create_cohort
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  items= pd.read_csv(self.mimic_path+'/icu/d_items.csv.gz',compression='gzip', header=0)
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  with open(filepath, 'rb') as fp:
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  dico = pickle.load(fp)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ for key, data in dico.items():
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+ cond_text,chart_text,meds_text,proc_text,out_text = self.generate_text(data,icd,items, self.feat_cond, self.feat_chart, self.feat_meds, self.feat_proc, self.feat_out)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  yield int(key),{
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  'label' : data['label'],
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+ 'text': cond_text+chart_text+meds_text+proc_text+out_text
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  }
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  #############################################################################################################################