mahbeigom / patients-readmission-classification-project Goto Github PK

For this project, the dataset used is the UCI dataset. The dataset (diabetic_data.csv) represents 10 years (1999-2008) of clinical care at 130 US hospitals and integrated delivery networks.

The dataset contains 50 explanatory variables that describe the patient and hospital outcomes. We predict the readmission of a patient discharged from a hospital within 30 days, based on the given dataset. The data is preprocessed, split into a train and test data set for training and testing purposes. The training and test set have been taken from this folder.

The primary objective of this project's predictive analysis is to build a binary classification model that can predict early (<30 days) readmission given the patient’s features i.e. - To predict whether a patient will be readmitted in hospital given that they have been discharged from the hospital in the last 30 days.