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Screening for patients at risk for cardiac amyloidosis via electronic health records: A multicenter machine learning development and validation study
Timely detection is crucial to improve outcomes in patients with cardiac amyloidosis (CA) by initiation of guideline-directed disease-modifying treatments. Although confirmatory bone scintigraphy is highly accurate for CA detection, identifying at-risk patients for referral remains challenging. Thi
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