A Predictive Analytics Methodology to Assess and Optimize Readmission Risk in Heart Failure Patients

A Predictive Analytics Methodology to Assess and Optimize Readmission Risk in Heart Failure Patients
Title:
A Predictive Analytics Methodology to Assess and Optimize Readmission Risk in Heart Failure Patients
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AAAI-18: Thirty-Second AAAI Conference on Artificial Intelligence
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Publication Date:
03 February 2018
Citation:
Abstract:
We describe a predictive modeling and decision support framework that integrates machine learning and optimization for personalized clinical decision support. We pilot the approach on data from a congestive heart failure patient cohort, and demonstrate the ability to predict and optimize readmission risk in a clinically meaningful manner.
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