Mount Sinai researchers use new deep learning approach to enable analysis of electrocardiograms as language
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| June 07, 2023
“These representations may be considered individual words, and the whole ECG a single document,” explains Dr. Vaid. “HeartBEiT understands the relationships between these representations and uses this understanding to perform downstream diagnostic tasks more effectively. The three tasks we tested the model on were learning if a patient is having a heart attack, if they have a genetic disorder called hypertrophic cardiomyopathy, and how effectively their heart is functioning. In each case, our model performed better than all other tested baselines.”
Researchers pretrained HeartBEiT on 8.5 million ECGs from 2.1 million patients collected over four decades from four hospitals within the Mount Sinai Health System. Then they tested its performance against standard CNN architectures in the three cardiac diagnostic areas. The study found that HeartBEiT had significantly higher performance at lower sample sizes, along with better “explainability.” Elaborates senior author Girish Nadkarni, MD, MPH, Irene and Dr. Arthur M. Fishberg Professor of Medicine at Icahn Mount Sinai, Director of The Charles Bronfman Institute of Personalized Medicine, and System Chief, Division of Data-Driven and Digital Medicine, Department of Medicine: “Neural networks are considered black boxes, but our model was much more specific in highlighting the region of the ECG responsible for a diagnosis, such as a heart attack, which helps clinicians to better understand the underlying pathology. By comparison, the CNN explanations were vague even when they correctly identified a diagnosis.”
Indeed, through its sophisticated new modeling architecture, the Mount Sinai team has greatly enhanced the manner and opportunities by which physicians can interact with the ECG. “We want to be clear that artificial intelligence is by no means replacing diagnosis by professionals from ECGs,” explained Dr. Nadkarni, “but rather augmenting the ability of that medium in an exciting and compelling new way to detect heart problems and monitor the heart’s health.”
The paper is titled “A foundational vision transformer improves diagnostic performance for electrocardiograms.”
About the Icahn School of Medicine at Mount Sinai
The Icahn School of Medicine at Mount Sinai is internationally renowned for its outstanding research, educational, and clinical care programs. It is the sole academic partner for the eight- member hospitals* of the Mount Sinai Health System, one of the largest academic health systems in the United States, providing care to a large and diverse patient population.
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