Classification of intensive care patient data
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Patient Data Predictive Modeling

Authors: Brandon Carter and Angie Boggust

Massachusetts Institute of Technology
Leiden Institute of Advanced Computer Science
The goal of this project was to use a bank of patient data from the intensive care unit to determine whether patients received a transfusion as well as which patient features are most critical in the classification. This code addresses the problem using a variety of predictive classification models from scikit-learn. It also provides tools for data parsing, statistical analysis, graphing, and PDF output of decision tree models.

We unfortunately cannot publish any data associated with this database and have anonymized attribute and string names from within the data schema. However, this code shows the skeleton used as part of our analysis of the data and the goal of predictive classification of the patient data.