Machine learning models for atrial fibrillation detection in primary care using electronic health records: systematic review [Cardiovascular disease]
Annals of Family Medicine
NOVEMBER 20, 2024
Context: Atrial fibrillation (AFib) significantly impacts patient morbidity and mortality, despite existing screening practices. Machine learning (ML) models offer potential for improved detection of AFib from electronic health records (EHR). Models combining ML with other clinical tools showed improved discrimination.
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