""""
fetching and processing electronic medical reports
"""
import pandas as pd
from clintk.utils.connection import get_engine, sql2df
from clintk.utils.fold import Folder
from clintk.text_parser.parser import ReportsParser
import argparse
def fetch_and_fold(table, engine, targets, n_reports):
""" function to fetch reports from vcare database
Parameters
----------
For definition of parameters, see arguments in `main_fetch_and_fold`
"""
key1, key2, date = 'patient_id', 'nip', 'date'
# data used to train the model
df_targets = sql2df(engine, targets).loc[:, ['nip', 'id', 'C1J1']]
df_targets.loc[:, 'C1J1'] = pd.to_datetime(df_targets['C1J1'],
format='%Y-%m-%d',
unit='D')
df_reports = sql2df(engine, table)\
.loc[:, ['original_date', 'patient_id', 'report']]
mask = [report is not None for report in df_reports['report']]
df_reports.rename(columns={'original_date': 'date'}, inplace=True)
df_reports = df_reports.loc[mask]
# joining features df with complete patient informations
df_reports = df_reports.merge(df_targets, on=None, left_on='patient_id',
right_on='id').drop('id', axis=1)
# df_reports = df_reports[df_reports[date] <= df_reports['C1J1']]
# folding frames so that they have the same columns
folder = Folder(key1, key2, ['report'], date, n_jobs=-1)
reports_folded = folder.fold(df_reports)
reports_folded.dropna(inplace=True)
reports_folded.drop_duplicates(subset=['value'], inplace=True)
# taking only first `n_reports` reports
group_dict = {key2: 'first', 'feature': 'first', date: 'last',
'value': lambda g: ' '.join(g[:n_reports])}
reports_folded = reports_folded.groupby(key1, as_index=False)\
.agg(group_dict)
# parsing and vectorising text reports
sections = ['examens complementaire', 'hopital de jour',
'examen du patient']
parser = ReportsParser(sections=None, n_jobs=-1, norm=False,
col_name='value')
reports_folded['value'] = parser.transform(reports_folded)
return reports_folded
def main_fetch_and_fold():
description = 'Folding text reports from Ventura Care'
parser = argparse.ArgumentParser(description=description)
parser.add_argument('--reports', '-r',
help='name of the table contains the reports')
parser.add_argument('--id', '-I',
help='id to connect to sql server')
parser.add_argument('--ip', '-a',
help='ip address of the sql server')
parser.add_argument('--db', '-d',
help='name of the database on the sql server')
parser.add_argument('--targets', '-t',
help='name of the table containing targets on the db')
parser.add_argument('--output', '-o',
help='output path to write the folded result')
parser.add_argument('-n', '--nb',
help='number of reports to fetch', type=int)
args = parser.parse_args()
# getting variables from args
engine = get_engine(args.id, args.ip, args.db)
reports_folded = fetch_and_fold(args.reports, engine, args.targets, args.nb)
output = args.output
reports_folded.to_csv(output, encoding='utf-8', sep=';')
print('done')
return reports_folded
if __name__ == "__main__":
main_fetch_and_fold()
