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ECG-based AI could reduce hospital mortality

An artificial intelligence (AI) system that sends text messages to alert hospital physicians about the high risk for mortality in their patients reduces the number of deaths, according to a study published in Nature Medicine.

Chin-Sheng Lin, PhD, associate professor of cardiology at the Tri-Service General Hospital of the National Defense Medical Center in Taipei, Taiwan, and his colleagues have developed an AI system that identifies patients with a high risk for mortality on the basis of a 12-lead ECG. The system is intended to identify patients who would benefit from intensified care.

"It is widely acknowledged that providing intensive care to critically ill patients reduces mortality. Delays in providing intensive care for critically ill patients result in catastrophic outcomes. Most in-hospital cardiac arrests are potentially preventable; however, the early signs of deterioration might be difficult to identify," wrote the researchers.

The authors emphasized that exactly how the AI warning messages lead to a decrease in overall mortality must still be clarified. But the results suggest that they help in detecting high-risk patients, triggering timely clinical care, and reducing mortality, they wrote.

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Source: Medscape, 21 May 2024


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