{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:50:56Z","timestamp":1785419456375,"version":"3.56.0"},"reference-count":35,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T00:00:00Z","timestamp":1746576000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["jacc.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["JACC: Asia"],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1016\/j.jacasi.2025.03.015","type":"journal-article","created":{"date-parts":[[2025,6,10]],"date-time":"2025-06-10T14:06:16Z","timestamp":1749564376000},"page":"865-880","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"title":["Developing an ML-Based Pretest Probability Model of Obstructive CAD in Patients With Stable Chest Pain"],"prefix":"10.1016","volume":"5","author":[{"given":"Guanhua","family":"Dou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqiang","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1453-608X","authenticated-orcid":false,"given":"Dongkai","family":"Shan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinghua","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8499-0448","authenticated-orcid":false,"given":"Lei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xudong","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junjie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yundai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.jacasi.2025.03.015_bib1","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.amjcard.2012.10.029","article-title":"Diagnostic performance of computed tomography coronary angiography (from the Prospective National Multicenter Multivendor Evascan Study)","volume":"111","author":"Gueret","year":"2013","journal-title":"Am J Cardiol"},{"issue":"1","key":"10.1016\/j.jacasi.2025.03.015_bib2","doi-asserted-by":"crossref","first-page":"9228","DOI":"10.1038\/s41598-018-27347-8","article-title":"Diagnostic yield and accuracy of coronary CT angiography after abnormal nuclear myocardial perfusion imaging","volume":"8","author":"Meinel","year":"2018","journal-title":"Sci Rep"},{"issue":"11","key":"10.1016\/j.jacasi.2025.03.015_bib3","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1016\/j.jcmg.2015.06.016","article-title":"Hs-troponin I followed by CT angiography improves acute coronary syndrome risk stratification accuracy and work-up in acute chest pain patients: results from Romicat Ii Trial","volume":"8","author":"Ferencik","year":"2015","journal-title":"JACC Cardiovasc Imaging"},{"issue":"14","key":"10.1016\/j.jacasi.2025.03.015_bib4","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1056\/NEJMoa1415516","article-title":"Outcomes of anatomical versus functional testing for coronary artery disease","volume":"372","author":"Douglas","year":"2015","journal-title":"N Engl J Med"},{"issue":"2","key":"10.1016\/j.jacasi.2025.03.015_bib5","first-page":"113","article-title":"Research progress of models of pre-test probability for obstructive coronary heart disease","volume":"21","author":"Wang","year":"2021","journal-title":"Cardio-Cerebrovasc Dis Prev Treat"},{"issue":"11","key":"10.1016\/j.jacasi.2025.03.015_bib6","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1093\/ehjci\/jez054","article-title":"Impact of a decreasing pre-test probability on the performance of diagnostic tests for coronary artery disease","volume":"20","author":"Juarez-Orozco","year":"2019","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"3","key":"10.1016\/j.jacasi.2025.03.015_bib7","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1093\/eurheartj\/ehz425","article-title":"2019 Esc guidelines for the diagnosis and management of chronic coronary syndromes","volume":"41","author":"Knuuti","year":"2020","journal-title":"Eur Heart J"},{"issue":"11","key":"10.1016\/j.jacasi.2025.03.015_bib8","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1093\/ehjci\/jez058","article-title":"Pre-test probability prediction in patients with a low to intermediate probability of coronary artery disease: a prospective study with a fractional flow reserve endpoint","volume":"20","author":"Winther","year":"2019","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"9","key":"10.1016\/j.jacasi.2025.03.015_bib9","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1016\/j.jcmg.2018.06.021","article-title":"Comparison of international guidelines for assessment of suspected stable angina: insights from the promise and SCOT-HEART","volume":"11","author":"Adamson","year":"2018","journal-title":"JACC Cardiovasc Imaging"},{"issue":"3","key":"10.1016\/j.jacasi.2025.03.015_bib10","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1093\/eurheartj\/ehz565","article-title":"Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the Confirm Registry","volume":"41","author":"Al'aref","year":"2020","journal-title":"Eur Heart J"},{"issue":"8","key":"10.1016\/j.jacasi.2025.03.015_bib11","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1016\/j.amjmed.2014.10.031","article-title":"Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease","volume":"128","author":"Min","year":"2015","journal-title":"Am J Med"},{"issue":"21","key":"10.1016\/j.jacasi.2025.03.015_bib12","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.1016\/j.jacc.2020.09.585","article-title":"Incorporating coronary calcification into pre-test assessment of the likelihood of coronary artery disease","volume":"76","author":"Winther","year":"2020","journal-title":"J Am Coll Cardiol"},{"issue":"7","key":"10.1016\/j.jacasi.2025.03.015_bib13","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1097\/CM9.0000000000001307","article-title":"Rationale, Design, and baseline characteristics of Chinese Registry in Early Detection and Risk Stratification of Coronary Plaques (C-Strat) study","volume":"134","author":"Yang","year":"2021","journal-title":"Chin Med J (Engl)"},{"issue":"1","key":"10.1016\/j.jacasi.2025.03.015_bib14","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1146\/annurev-clinpsy-080822-051727","article-title":"Missing data analysis","volume":"20","author":"Little","year":"2024","journal-title":"Annu Rev Clin Psychol"},{"issue":"2","key":"10.1016\/j.jacasi.2025.03.015_bib15","doi-asserted-by":"crossref","first-page":"191","DOI":"10.3349\/ymj.2019.60.2.191","article-title":"Machine learning for the prediction of new-onset diabetes mellitus during 5-year follow-up in non-diabetic patients with cardiovascular risks","volume":"60","author":"Choi","year":"2019","journal-title":"Yonsei Med J"},{"issue":"36","key":"10.1016\/j.jacasi.2025.03.015_bib16","doi-asserted-by":"crossref","first-page":"3415","DOI":"10.1093\/eurheartj\/ehae177","article-title":"2024 ESC guidelines for the management of chronic coronary syndromes","volume":"45","author":"Vrints","year":"2024","journal-title":"Eur Heart J"},{"key":"10.1016\/j.jacasi.2025.03.015_bib17","article-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017","journal-title":"ArXiv"},{"key":"10.1016\/j.jacasi.2025.03.015_bib18","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/1472-6947-8-53","article-title":"Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers","volume":"8","author":"Vickers","year":"2008","journal-title":"BMC Med Inform Decis Mak"},{"issue":"2","key":"10.1016\/j.jacasi.2025.03.015_bib19","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1161\/01.CIR.64.2.360","article-title":"Angiographic prevalence of high-risk coronary artery disease in patient subsets (Cass)","volume":"64","author":"Chaitman","year":"1981","journal-title":"Circulation"},{"issue":"11","key":"10.1016\/j.jacasi.2025.03.015_bib20","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.1093\/eurheartj\/ehr014","article-title":"A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension","volume":"32","author":"Genders","year":"2011","journal-title":"Eur Heart J"},{"issue":"11","key":"10.1016\/j.jacasi.2025.03.015_bib21","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1093\/ehjci\/jez054","article-title":"Impact of a decreasing pre-test probability on the performance of diagnostic tests for coronary artery disease","volume":"20","author":"Juarez-Orozco","year":"2019","journal-title":"Eur Heart J Cardiovasc Imaging"},{"key":"10.1016\/j.jacasi.2025.03.015_bib22","article-title":"Validation of the European Society of Cardiology pre-test probability model for obstructive coronary artery disease","volume":"42","author":"Winther","year":"2021","journal-title":"Eur Heart J"},{"issue":"3","key":"10.1016\/j.jacasi.2025.03.015_bib23","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1007\/s00330-020-07175-z","article-title":"Clinical pre-test probability for obstructive coronary artery disease: insights from the European Discharge Pilot Study","volume":"31","author":"Feger","year":"2021","journal-title":"Eur Radiol"},{"issue":"5","key":"10.1016\/j.jacasi.2025.03.015_bib24","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1093\/ehjci\/jey182","article-title":"Pretest probability for patients with suspected obstructive coronary artery disease: re-evaluating Diamond-Forrester for the contemporary era and clinical implications: insights from the PROMISE trial","volume":"20","author":"Foldyna","year":"2019","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"18","key":"10.1016\/j.jacasi.2025.03.015_bib25","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1161\/CIRCULATIONAHA.123.063996","article-title":"On-site computed tomography-derived fractional flow reserve to guide management of patients with stable coronary artery disease: the TARGET randomized trial","volume":"147","author":"Yang","year":"2023","journal-title":"Circulation"},{"issue":"17","key":"10.1016\/j.jacasi.2025.03.015_bib26","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1056\/NEJMoa2200963","article-title":"CT or invasive coronary angiography in stable chest pain","volume":"386","author":"Maurovich-Horvat","year":"2022","journal-title":"N Engl J Med"},{"issue":"Suppl 1","key":"10.1016\/j.jacasi.2025.03.015_bib27","article-title":"Prediction of coronary artery disease in positron emission tomography using machine learning algorithms with clinical data and calcium score","volume":"22","author":"Clerc","year":"2021","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"1","key":"10.1016\/j.jacasi.2025.03.015_bib28","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCIMAGING.118.008002","article-title":"Epicardial fat volume improves the prediction of obstructive coronary artery disease above traditional risk factors and coronary calcium score development and validation of new pretest probability models in Chinese populations","volume":"12","author":"Zhou","year":"2019","journal-title":"Circ Cardiovasc Imaging"},{"key":"10.1016\/j.jacasi.2025.03.015_bib29","doi-asserted-by":"crossref","DOI":"10.1093\/ehjci\/jeaa356.233","article-title":"ESC 2019 guidelines on chronic coronary syndromes: can calcium scoring improve the risk underestimation associated with the updated pre-test probability risk score?","volume":"22","author":"Fyyaz","year":"2021","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"12","key":"10.1016\/j.jacasi.2025.03.015_bib30","doi-asserted-by":"crossref","first-page":"2584","DOI":"10.1016\/j.jcmg.2019.07.030","article-title":"Machine learning for pretest probability of obstructive coronary stenosis in symptomatic patients","volume":"12","author":"Hou","year":"2019","journal-title":"JACC Cardiovasc Imaging"},{"issue":"4","key":"10.1016\/j.jacasi.2025.03.015_bib31","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.jcct.2017.05.004","article-title":"Validation and comparison of 4 models to calculate pretest probability of obstructive coronary artery disease in a Chinese population: a coronary computed tomographic angiography study","volume":"11","author":"Zhou","year":"2017","journal-title":"J Cardiovasc Comput Tomogr"},{"issue":"4","key":"10.1016\/j.jacasi.2025.03.015_bib32","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.jelectrocard.2018.03.008","article-title":"ECG markers of arrythmogenic risk relationships with pericardial fat volume and BMI in patients with coronary atherosclerosis","volume":"51","author":"Al-Mosawi","year":"2018","journal-title":"J Electrocardiol"},{"issue":"5","key":"10.1016\/j.jacasi.2025.03.015_bib33","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1177\/0003319717715579","article-title":"High resting heart rate and high BMI predicted severe coronary atherosclerosis burden in patients with stable angina pectoris by Syntax Score","volume":"69","author":"Zhang","year":"2018","journal-title":"Angiology"},{"key":"10.1016\/j.jacasi.2025.03.015_bib34","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.ijcard.2023.05.041","article-title":"Pre-test probability for coronary artery disease in patients with chest pain based on machine learning techniques","volume":"385","author":"Choi","year":"2023","journal-title":"Int J Cardiol"},{"issue":"7 Pt 2","key":"10.1016\/j.jacasi.2025.03.015_bib35","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.1016\/j.jcmg.2018.02.020","article-title":"A comparison of the updated Diamond-Forrester, CAD Consortium, and CONFIRM history-based risk scores for predicting obstructive coronary artery disease in patients with stable chest pain: the SCOT-HEART Coronary CTA Cohort","volume":"12","author":"Baskaran","year":"2019","journal-title":"JACC Cardiovasc Imag"}],"container-title":["JACC: Asia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772374725002625?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772374725002625?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T16:18:56Z","timestamp":1752596336000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2772374725002625"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":35,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["S2772374725002625"],"URL":"https:\/\/doi.org\/10.1016\/j.jacasi.2025.03.015","relation":{},"ISSN":["2772-3747"],"issn-type":[{"value":"2772-3747","type":"print"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Developing an ML-Based Pretest Probability Model of Obstructive CAD in Patients With Stable Chest Pain","name":"articletitle","label":"Article Title"},{"value":"JACC: Asia","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jacasi.2025.03.015","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.","name":"copyright","label":"Copyright"}]}}