NetworkNewsBreaks – HeartBeam Inc. (NASDAQ: BEAT
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HeartBeam (NASDAQ: BEAT), a medical technology company focused on transforming cardiac care through the power of personalized insights, today announced the results of a new study demonstrating that HeartBeam AI combined with vectorcardiography (“VCG”) outperformed an expert panel of heart rhythm cardiologists in detecting atrial flutter. Key findings from the analysis show that HeartBeam AI combined with VCG outperformed an expert panel reviewing single-lead ECGs and demonstrated a statistically significant 6% improvement in the detection of atrial flutter cases compared to an expert panel reviewing 12-lead ECGs. “The modern vectorcardiogram is nearly 100 years old, and yet we are cautiously breathing new life into it with the advent of novel acquisition technologies and deep learning algorithms. This study demonstrates that a deep learning algorithm applied to a transformed VCG performs comparably as well when applied to the gold-standard 12-lead ECG,” said Joshua M. Lampert, MD, who presented the data during the Heart Rhythm Society annual meeting in Boston. Dr. Lampert is a cardiac electrophysiologist, assistant professor of medicine, and medical director of machine learning for Mount Sinai Fuster Heart Hospital at the Icahn School of Medicine at Mount Sinai. “The AI algorithm overall outperformed a panel of electrophysiologists in distinguishing atrial flutter from sinus rhythm with perfect agreement between multiple model predictions compared to significant interobserver variability amongst electrophysiologists, a finding particularly notable on single lead ECG analysis.”
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