Can machine learning improve patient selection for cardiac resynchronization therapy?

Szu-Yeu HuEnrico SantusAlexander W ForsythDevvrat MalhotraJosh HaimsonNeal A ChatterjeeDaniel B KramerRegina BarzilayJames A TulskyCharlotta Lindvall

Published in: PloS one (2019)

A machine learning model that leveraged readily available EHR data and clinical notes identified a subset of CRT patients who may not benefit from CRT before the procedure.

Keyphrases

cardiac resynchronization therapy
machine learning
left ventricular
heart failure
big data
electronic health record
artificial intelligence
case report
minimally invasive
deep learning
atrial fibrillation