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Machine learning can help predict the risk of heart failure in diabetes patients

This risk tool is an important step in the right direction to promote prevention of heart failure in patients with type 2 diabetes

Machine Learning Informs a New Tool to Guide Treatment for Acute Decompensated Heart Failure

Machine learning could personalize diuretic treatment for patients with 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).

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