2025 Super Doctors - Southern California - S-6

SOUTHERN CALIFORNIA SUPER DOCTORS 2025
UTH RN CA
6
Predicting the deadliest heart disease
Sudden cardiac arrest claims more
than 436,000 lives annually in the
U.S., according to the American Heart
Association. The condition disrupts the
heart's electrical activity, causing a sudden
stop. It's fatal in 90% of cases and affects
those with and without known heart
issues. Two recent studies at the Smidt
Heart Institute showcase AI's potential to
predict sudden cardiac arrest-a medical
emergency that to date has been hard to
reliably forecast.
Sumeet Chugh, MD, director of the Division
of Artificial Intelligence in Medicine at
Cedars-Sinai, says that preventing sudden
cardiac arrest is crucial but challenging,
and AI could be a game-changer. AI might
help doctors identify patients at higher risk
for this condition.
In a study featured in Communications
Medicine, researchers, including Dr.
Ouyang and Dr. Chugh, taught a deep
learning algorithm to, in short, analyze
patterns in ECGs that display the heart's
electrical activity. The finding: The AI model
was more accurate in predicting who would
suffer from sudden cardiac arrest than the
traditional ECG risk score method.
A second study, published
in January 2024 in
Circulation: Arrhythmia
and Electrophysiology,
involves an AI model that
distinguishes between two
causes of sudden cardiac
arrest-pulseless electrical
activity and ventricular
fibrillation. Pulseless electrical
activity can't be treated with
a defibrillator, often leading
to death, while ventricular
fibrillation can be treated
with a defibrillator shock.
Identifying which patients are
prone to each type through AI
could save lives.
This AI model was trained
to review ECG patterns and
patient traits, then identify
risk factors for each type of
cardiac arrest. Researchers
learned that those with
pulseless electrical activity
This supplement is printed and distributed by the Los Angeles Times Media Group. It did not involve the editorial or reporting staffs of the Los Angeles Times.
were often older, overweight, had anemia,
or experienced shortness of breath.
Meanwhile, ventricular fibrillation victims
RN
SUPER DOCTORS 2025
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2025 Super Doctors - Southern California

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