Bioinformatics Commons^™

Applying Novel Tree-Based Frameworks To Big Data For Classification Of Heart Failure Patients And Prediction Of Clinical Responses, Yan Zhang, Nicholas Downing, Emily Bucholz, Suganthi Balasubramanian, Shu-Xia Li, Tara Liptak, Harlan Krumholz, Mark Gerstein

Yale Day of Data

Over 5 million Americans suffer from heart failure, a condition with a 5-year survival that eclipses all cancers apart from that of lung cancer. Conventional understanding of heart failure is simplistic: it is viewed as a single syndrome, despite real heterogeneity. In addition, models predicting outcomes focus on dichotomous results, like 30-day readmission. A novel approach to classification of heart failure may improve our ability to target interventions, improve patient experiences, and predict outcomes.

The Healthcare Cost and Utilization Project is a family of administrative claims databases that describes patient demographics, comorbidities, procedures, acute care utilization and outcomes, such as …