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Using MIMIC II dataset & primitive NLP techniques to asses the impact of notes sentiment on patient mortality

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HealthCare Analytics

Course Project for BM60130 taught at IIT Kharagpur

Mining Clinical Notes for Mortality Prediction

Unstructured clinical data such as nursing notes are very less used to build a predictive model for post-discharge mortality despite containing rich information. Our work examines a simple bag of words model approach for 7/30/180/365 day mortality prediction. We also explored syntactic sentiment dimensions from these nursing notes as a predictor of mortality, and report preliminary survival analysis results too. Our simple BOW model using XGBoost achieved 0.92 AUC for 30-day mortality.

Link to Project Report is here

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Using MIMIC II dataset & primitive NLP techniques to asses the impact of notes sentiment on patient mortality

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