Prediction of hospitalization due to heart diseases by supervised learning methods. Issue 3 (March 2015) - Dai, Wuyang; Brisimi, Theodora S.; Adams, William G.; Mela, Theofanie; Saligrama, Venkatesh; Paschalidis, Ioannis Ch.
Highlights Using the EHR, it is possible to accurately predict heart-related hospitalizations. Machine learning methods improve prediction accuracy over existing risk metrics. A novel Likelihood Ratio Test provides prediction accuracy and interpretability. Implementing such methods can lead to improved care and drastic cost savings.