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The Shakespeare-Method repository contains the code we used to develop a new method to identify attributed and unattributed potential adverse events using the unstructured notes portion of electronic health records.

License: GNU General Public License v3.0

Jupyter Notebook 30.27% HTML 69.73%
topic-modeling python postgres latent-dirichlet-allocation scikit-learn mimic-iii ehr-notes ehr medical adverse-events

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shakespeare-method's Issues

what database?

before executing the notebook 1.0_create_adult_inputs.ipynb I have created a database as follows:
make mimic datadir="/media/joepareti54/Elements/x/finance-2021/AI/NLP/Shakespeare-Booz-Allen/physionet.org/files/mimiciii-demo/1.4/" DBNAME="joepareti54" DBPASS="***โ€

and then changed the notebook:
from sqlalchemy import create_engine, update conn = psycopg2.connect("dbname=joepareti54 user=postgres \ password=**** options=--search_path=mimiciii"); engine = create_engine('postgresql://joepareti54:****@localhost/mimiciii') cur = conn.cursor(); cur.execute("""SET search_path = mimiciii;""")

because I do not have the variables
POSTGRES_CONNECT = os.environ.get("POSTGRES_CONNECT") POSTGRES_ENGINE = os.environ.get("POSTGRES_ENGINE")

The notebook runs although the data is different than here

The notebook 1.1a_create_transfused_cohort.ipynb however throws an invalid syntax exception, and I believe it does not find any transfusion case:

COPY mimiciii.transfusion_items_dict FROM 'D:\\20180717D_ITEMS_related_to_blood_full.csv' DELIMITER ',' CSV HEADER;

In summary, I need to identify the correct data-set and to fix the above code. More information here.

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