Mount Sinai researchers developed an AI model to make individualized treatment recommendations for atrial fibrillation (AF) patients—helping clinicians accurately decide whether or not to treat them with anticoagulants (blood thinner medications) to prevent stroke, which is currently the standard treatment course in this patient population. This model presents a completely new approach for how clinical decisions are made for AF patients and could represent a potential paradigm shift in this area.
New AI model accurately identifies which atrial fibrillation patients need blood thinners to prevent stroke
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