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Table 3 Machine learning risk prediction studies in heart failure, acute coronary syndromes and atrial fibrillation (n = 57)

From: Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility

  1. ACS, acute coronary syndrome; AF, atrial fibrillation; Atherosclerosis Risk in Communities Study; CHARGE Cohorts for Heart and Aging Research in Genomic Epidemiology; CHA2DS2-VASc congestive heart failure, hypertension, age > 75, diabetes mellitus, stroke, vascular disease, sex category; CVD, cardiovascular disease; ECG, electrocardiogram; EHR, electronic health records; GRACE, Global Registry of Acute Coronary Events; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; IP, hospital inpatient; LV, left ventricular; OP, hospital outpatient; RCT, randomised controlled trial; TIMI, thrombolysis in myocardial infarction; UK, United Kingdom; US, United States
  2. *Australia, Austria, Brazil, Canada, China, Denmark, Korea, Finland, France, Germany, Italy, Japan, Mexico, Norway, Poland, Spain, Sweden, Netherlands, and UK
  3. ◦ Negative/no for all columns (except in the “Baseline population” column, where it denotes “unreported”)
  4. Positive/yes