{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T18:27:12Z","timestamp":1786991232472,"version":"build-2736575974"},"reference-count":25,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T00:00:00Z","timestamp":1719878400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","award":["PI20\/00587"],"award-info":[{"award-number":["PI20\/00587"]}],"id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["jacc.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["JACC: Advances"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1016\/j.jacadv.2024.101135","type":"journal-article","created":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T16:49:12Z","timestamp":1723654152000},"page":"101135","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":8,"special_numbering":"P2","title":["Machine Learning Prediction for Prognosis of Patients With Aortic\u00a0Stenosis"],"prefix":"10.1016","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8082-1567","authenticated-orcid":false,"given":"Sara","family":"Shimoni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9583-008X","authenticated-orcid":false,"given":"Ruslan","family":"Sergienko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Martinez-Legazpi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valery","family":"Meledin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sorel","family":"Goland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sagie","family":"Tshori","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob","family":"George","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier.","family":"Bermejo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lior","family":"Rokach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jacadv.2024.101135_bib1","doi-asserted-by":"crossref","first-page":"3515","DOI":"10.1093\/eurheartj\/ehw229","article-title":"Large-scale community echocardiographic screening reveals a major burden of undiagnosed valvular heart disease in older people: the OxVALVE Population Cohort Study","volume":"37","author":"d'Arcy","year":"2016","journal-title":"Eur Heart J"},{"key":"10.1016\/j.jacadv.2024.101135_bib2","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1001\/jama.2022.5776","article-title":"Effect of transcatheter aortic valve Implantation vs surgical aortic valve replacement on all-cause mortality in patients with aortic stenosis: a randomized clinical trial","volume":"327","author":"Investigators","year":"2022","journal-title":"JAMA"},{"key":"10.1016\/j.jacadv.2024.101135_bib3","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0268580","article-title":"Increasing risk of mortality across the spectrum of aortic stenosis is independent of comorbidity & treatment: an international, parallel cohort study of 248,464 patients","volume":"17","author":"Strom","year":"2022","journal-title":"PLoS One"},{"key":"10.1016\/j.jacadv.2024.101135_bib4","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1093\/ehjci\/jeac003","article-title":"Transvalvular jet velocity, aortic valve area, mortality, and cardiovascular outcomes","volume":"23","author":"Alcon","year":"2022","journal-title":"Eur Heart J Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib5","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.jcmg.2018.04.026","article-title":"Predicting survival from large echocardiography and electronic Health record datasets: optimization with machine learning","volume":"12","author":"Samad","year":"2019","journal-title":"JACC Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib6","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1016\/j.jcmg.2021.03.020","article-title":"A\u00a0machine-learning framework to identify distinct phenotypes of aortic stenosis severity","volume":"14","author":"Sengupta","year":"2021","journal-title":"JACC Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/ejechocard\/jen303","article-title":"Echocardiographic assessment of valve stenosis: EAE\/ASE recommendations for clinical practice","volume":"10","author":"Baumgartner","year":"2009","journal-title":"Eur J Echocardiogr"},{"key":"10.1016\/j.jacadv.2024.101135_bib8","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1093\/ehjci\/jew335","article-title":"Recommendations on the echocardiographic assessment of aortic valve stenosis: a focused update from the European Association of Cardiovascular Imaging and the American Society of Echocardiography","volume":"18","author":"Baumgartner","year":"2017","journal-title":"Eur Heart J Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib9","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1161\/CIRCIMAGING.113.001375","article-title":"Aortic stenosis suspected to be severe despite low gradients","volume":"7","author":"Pibarot","year":"2014","journal-title":"Circ Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib10","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1093\/ejechocard\/jeq031","article-title":"European Association of Echocardiography recommendations for the assessment of valvular regurgitation. Part 2: mitral and tricuspid regurgitation (native valve disease)","volume":"11","author":"Lancellotti","year":"2010","journal-title":"Eur J Echocardiogr"},{"key":"10.1016\/j.jacadv.2024.101135_bib11","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1093\/ehjci\/jev014","article-title":"Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging","volume":"16","author":"Lang","year":"2015","journal-title":"Eur Heart J Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib12","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1016\/j.amjcard.2015.12.010","article-title":"Effect of mitral annular calcium on left ventricular diastolic parameters","volume":"117","author":"Codolosa","year":"2016","journal-title":"Am J Cardiol"},{"key":"10.1016\/j.jacadv.2024.101135_bib13","article-title":"Random survival forests with multivariate longitudinal endogenous covariates","year":"2023","journal-title":"arXiv"},{"key":"10.1016\/j.jacadv.2024.101135_bib14","doi-asserted-by":"crossref","DOI":"10.1155\/2013\/873595","article-title":"A\u00a0gradient boosting algorithm for survival analysis via direct optimization of concordance index","volume":"2013","author":"Chen","year":"2013","journal-title":"Comput Math Methods Med"},{"key":"10.1016\/j.jacadv.2024.101135_bib15","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1136\/heartjnl-2021-319697","article-title":"Incident aortic stenosis in 49 449 men and 42 229 women investigated with routine echocardiography","volume":"108","author":"Stewart","year":"2022","journal-title":"Heart"},{"key":"10.1016\/j.jacadv.2024.101135_bib16","doi-asserted-by":"crossref","first-page":"1862","DOI":"10.1093\/eurheartj\/ehad121","article-title":"Unmet needs in valvular heart disease","volume":"44","author":"Messika-Zeitoun","year":"2023","journal-title":"Eur Heart J"},{"key":"10.1016\/j.jacadv.2024.101135_bib17","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-02476-9","article-title":"Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study","volume":"11","author":"Madakkatel","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.jacadv.2024.101135_bib18","doi-asserted-by":"crossref","DOI":"10.1136\/openhrt-2022-001990","article-title":"Predicting outcomes in patients with aortic stenosis using machine learning: the Aortic Stenosis Risk (ASteRisk) score","volume":"9","author":"Namasivayam","year":"2022","journal-title":"Open Heart"},{"key":"10.1016\/j.jacadv.2024.101135_bib19","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCIMAGING.119.009707","article-title":"Unsupervised cluster analysis of patients with aortic stenosis reveals distinct population with different phenotypes and outcomes","volume":"13","author":"Kwak","year":"2020","journal-title":"Circ Cardiovasc Imaging"},{"key":"10.1016\/j.jacadv.2024.101135_bib20","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1186\/s40364-017-0111-x","article-title":"Critical appraisal of the role of serum albumin in cardiovascular disease","volume":"5","author":"Chien","year":"2017","journal-title":"Biomark Res"},{"key":"10.1016\/j.jacadv.2024.101135_bib21","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.1093\/eurjpc\/zwac016","article-title":"Association of serum levels of calcium, phosphate, and vitamin D with risk of developing aortic stenosis: the UK Biobank cohort","volume":"29","author":"Xia","year":"2022","journal-title":"Eur J Preventive Cardiol"},{"key":"10.1016\/j.jacadv.2024.101135_bib22","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1111\/joim.12593","article-title":"Mortality from aortic stenosis: prospective study of serum calcium and phosphate","volume":"281","author":"Wald","year":"2017","journal-title":"J\u00a0Internal Med"},{"key":"10.1016\/j.jacadv.2024.101135_bib23","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.210064","article-title":"External validation of deep learning algorithms for radiologic diagnosis: a systematic review","volume":"4","author":"Yu","year":"2022","journal-title":"Radiol Artificial Intelligence"},{"key":"10.1016\/j.jacadv.2024.101135_bib24","doi-asserted-by":"crossref","first-page":"3351","DOI":"10.1093\/eurheartj\/ehx381","article-title":"Staging classification of aortic stenosis based on the extent of cardiac damage","volume":"38","author":"Genereux","year":"2017","journal-title":"Eur Heart J"},{"key":"10.1016\/j.jacadv.2024.101135_bib25","article-title":"Uncovering the phenotypic heterogeneity of patients with aortic stenosis: a path to new insights?","volume":"13","author":"Gayle","year":"2020","journal-title":"Circul Cardiovasc Imaging"}],"container-title":["JACC: Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772963X24003302?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772963X24003302?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T23:43:43Z","timestamp":1770162223000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2772963X24003302"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":25,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["S2772963X24003302"],"URL":"https:\/\/doi.org\/10.1016\/j.jacadv.2024.101135","relation":{},"ISSN":["2772-963X"],"issn-type":[{"value":"2772-963X","type":"print"}],"subject":[],"published":{"date-parts":[[2024,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Machine Learning Prediction for Prognosis of Patients With Aortic\u00a0Stenosis","name":"articletitle","label":"Article Title"},{"value":"JACC: Advances","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jacadv.2024.101135","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.","name":"copyright","label":"Copyright"}],"article-number":"101135"}}