AI Outperforms Doctors in predicting Cardiac Arrest, Could Save Lives
Baltimore, MD – A groundbreaking new artificial intelligence model is demonstrating significantly higher accuracy than doctors in identifying patients at risk of sudden cardiac arrest, offering the potential to save lives and reduce unneeded medical interventions. Developed by researchers at Johns Hopkins University,the AI analyzes a extensive range of medical data,including previously underutilized heart imaging,to reveal hidden indicators of heart health [[1]].
The research, published today in Nature Cardiovascular Research, focuses on hypertrophic cardiomyopathy, a common inherited heart disease affecting roughly 1 in 200-500 people globally and a leading cause of sudden cardiac death, particularly in young people and athletes [[1]]. Currently, identifying high-risk patients has proven challenging for clinicians.
“Currently we have patients dying in the prime of their life because they aren’t protected and others who are putting up with defibrillators for the rest of their lives with no benefit,” explains Natalia Trayanova, the senior author and a researcher specializing in AI in cardiology [[1]]. “We have the ability to predict with very high accuracy whether a patient is at very high risk for sudden cardiac death or not.”
Existing clinical guidelines used to assess risk have only about a 50%
