Scientists Show How AI May Spot Unseen Signs of Heart Failure

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A special artificial intelligence (AI)-based computer algorithm created by Mount Sinai researchers was able to learn how to identify subtle changes in electrocardiograms (also known as ECGs or EKGs) to predict whether a patient was experiencing heart failure.

The study was led by Akhil Vaid, MD, a postdoctoral scholar who works with Girish Nadkarni, MD, Associate Professor of Medicine at the Icahn School of Medicine at Mount Sinai, Clinical Director of the Hasso Plattner Institute for Digital Health, and Co-Director of the Mount Sinai Clinical Intelligence Center and Benjamin Glicksberg, PhD, Assistant Professor of Genetics and Genomic Sciences and a member of the Hasso Plattner Institute for Digital Health at the Icahn School of Medicine at Mount Sinai.

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Girish N. Nadkarni, MD, MPH, CPH
Associate Professor of Medicine
Icahn School of Medicine at Mount Sinai
Chief of the Division of Data-Driven and Digital Medicine (D3M)
Mount Sinai Health System

Benjamin Glicksberg, PhD
Assistant Professor of Genetics and Genomic Sciences
Hasso Plattner Institute for Digital Health
Icahn School of Medicine at Mount Sinai

Akhil Vaid, MD
Postdoctoral Schoolar
Hasso Plattner Institute for Digital Health
Icahn School of Medicine at Mount Sinai