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AI predicts if and when someone will experience cardiac arrest

24.11.2023 03:00 AM
AI predicts if and when someone will experience cardiac arrest
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AI predicts if and when someone will experience cardiac arrest
Artificial intelligence has undergone a significant advancement in the healthcare system in recent years, showing immense potential in enhancing care quality, reducing expenses, and securing a healthier future. One pivotal aspect of this progress lies in its capability to predict strokes.

Sudden cardiac arrest (SCA) stands as a global health concern, claiming the lives of 90% of its victims worldwide. In the United States alone, approximately 360,000 individuals succumb to SCA annually. Recent studies reveal that over half of patients experience warning signs hours or days before an episode of cardiac arrest. Unfortunately, due to patients neglecting these symptoms and medical personnel misinterpreting signs, a significant number of deaths occur.

According to media reports, Dr. "Traditional methods fall short in identifying individuals at high risk, particularly at the individual level."

However, a recent joint international scientific study, conducted by experts from various fields, suggests that artificial intelligence holds the potential to predict sudden cardiac arrest before its occurrence. This could significantly expedite necessary first aid and mitigate risks, as indicated by preliminary findings presented at the 2023 Resuscitation Sciences Symposium organized by the American Heart Association.

Utilizing artificial intelligence, researchers analyzed medical data from 25,000 sudden death cases and 70,000 hospitalizations due to heart attacks, among which patients survived, in Paris, France, and Seattle, Washington. Subsequently, they developed algorithms incorporating medical histories—like treatments for hypertension and prior heart disease—as well as mental and behavioral disorders, including alcohol abuse.

"We've been dedicated to predicting sudden cardiac death for nearly 30 years, but reaching this level of accuracy exceeded our expectations," remarked Xavier Goffin, a University of Paris medicine professor. He further emphasized, "We've also found that risk factors vary among individuals, blending neurological, psychological, metabolic, and cardiovascular data—a complex picture for doctors to navigate in predicting outcomes."

Despite these advancements, artificial intelligence, like any new field, has proponents advocating automation across the board, alongside concerns and apprehensions raised by many. One critical concern revolves around legal liability. In the event of a medical error, who assumes responsibility?
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