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Outcomes analysed were incident atrial fibrillation (AF), transient ischemic attack (TIA)\/stroke and mortality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>This study cohort included 706 patients, of whom 171 had normal inter\u2010atrial conduction, 257 had inter\u2010atrial block (IAB) and 266 had AF at baseline. Logistic regression analysis showed that age, hypertension and mean P\u2010wave duration (PWD) were significant predictors of new\u2010onset AF. Low left ventricular ejection fraction (LVEF), abnormal P\u2010wave terminal force in V1 (PTFV1) predicted TIA\/stroke. Age, smoking, hypertension, diabetes mellitus, hypercholesterolaemia, ischemic heart disease, secondary mitral regurgitation, urea, creatinine, NLR, PNI, left atrial diameter (LAD), left ventricular end\u2010diastolic dimension, LVEF, pulmonary arterial systolic pressure, IAB, baseline AF and heart failure predicted all\u2010cause mortality. A multi\u2010task Gaussian process learning model demonstrated significant improvement in risk stratification compared to logistic regression and a decision tree method.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A multi\u2010parametric approach incorporating multi\u2010modality clinical data improves risk stratification in mitral regurgitation. Multi\u2010task machine learning can significantly improve overall risk stratification performance.<\/jats:p><\/jats:sec>","DOI":"10.1111\/eci.13321","type":"journal-article","created":{"date-parts":[[2020,6,14]],"date-time":"2020-06-14T11:04:45Z","timestamp":1592132685000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Multi\u2010parametric system for risk stratification in mitral regurgitation: A multi\u2010task Gaussian prediction approach"],"prefix":"10.1111","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5510-1253","authenticated-orcid":false,"given":"Gary","family":"Tse","sequence":"first","affiliation":[{"name":"Tianjin Key Laboratory of Ionic\u2010Molecular Function of Cardiovascular disease Department of Cardiology Tianjin Institute of Cardiology Second Hospital of Tianjin Medical University  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiandong","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Data Science City University of Hong Kong  Kowloon Hong Kong SAR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharen","family":"Lee","sequence":"additional","affiliation":[{"name":"Laboratory of Cardiovascular Physiology Li Ka Shing Institute of Health Sciences  Hong Kong S.A.R. 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