Machine learning informs a new tool to guide treatment for acute decompensated heart failure
A recent study co-authored by Dr. Matthew Segar, a third-year cardiovascular disease fellow at The Texas Heart Institute and led by his research and residency mentor, University of Texas Southwestern Medical Center’s Dr. Ambarish Pandey, utilized a machine learning-based approach to identify, understand, and predict diuretic responsiveness in patients with acute decompensated heart failure (ADHF).
The study “A Phenomapping Tool and Clinical Score to Identify Low Diuretic Efficiency in Acute Decompensated ...












