{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T05:08:38Z","timestamp":1778821718956,"version":"3.51.4"},"reference-count":19,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","jacr.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of the American College of Radiology"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.jacr.2025.12.015","type":"journal-article","created":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T02:37:17Z","timestamp":1765593437000},"page":"809-817","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Learning Accelerator Framework: Scalable Clinical Artificial Intelligence Development and Delivery"],"prefix":"10.1016","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5408-2804","authenticated-orcid":false,"given":"Diana S.M.","family":"Buist","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Annie Y.","family":"Ng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bryan","family":"Haslam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5433-5824","authenticated-orcid":false,"given":"Edgar A.","family":"Wakelin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8185-7721","authenticated-orcid":false,"given":"Christoph I.","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sham","family":"Sokka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. Gregory","family":"Sorensen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.jacr.2025.12.015_bib2","author":"Angus"},{"key":"10.1016\/j.jacr.2025.12.015_bib11","author":"Newmarker"},{"key":"10.1016\/j.jacr.2025.12.015_bib12","author":"Gliadkovskaya"},{"key":"10.1016\/j.jacr.2025.12.015_bib15","doi-asserted-by":"crossref","DOI":"10.2196\/39742","article-title":"Technology Enhanced Macular Services Study Reference Group, et al. Stakeholder perspectives of clinical artificial intelligence implementation: systematic review of qualitative evidence","volume":"25","author":"Hogg","year":"2023","journal-title":"J Med Internet Res"},{"key":"10.1016\/j.jacr.2025.12.015_bib17","series-title":"Challenges associated with the adoption of artificial intelligence in medical device software","article-title":"Challenges associated with the adoption of artificial intelligence in medical device software","author":"Cepeda Zapata","year":"2023"},{"key":"10.1016\/j.jacr.2025.12.015_bib18","doi-asserted-by":"crossref","first-page":"207","DOI":"10.7326\/0003-4819-157-3-201208070-00012","article-title":"Implementing the learning health system: from concept to action","volume":"157","author":"Greene","year":"2012","journal-title":"Ann Intern Med"},{"key":"10.1016\/j.jacr.2025.12.015_bib19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1056\/NEJMp2103872","article-title":"Advancing the learning health system","volume":"385","author":"McGinnis","year":"2021","journal-title":"N Engl J Med"},{"key":"10.1016\/j.jacr.2025.12.015_bib21","series-title":"An AI-driven peer review quality-assurance process to improve cancer detection: real world experience in a community practice","author":"Aujero","year":"2023"},{"key":"10.1016\/j.jacr.2025.12.015_bib22","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.230137","article-title":"Impact of a categorical AI system for digital breast tomosynthesis on breast cancer interpretation by both general radiologists and breast imaging specialists","volume":"6","author":"Kim","year":"2024","journal-title":"Radiol Artif Intell"},{"key":"10.1016\/j.jacr.2025.12.015_bib24","doi-asserted-by":"crossref","DOI":"10.1038\/s44360-025-00001-0","article-title":"Equitable impact of an AI-driven breast cancer screening workflow in real world US-wide deployment","author":"Louis","year":"2025","journal-title":"Nature Health"},{"key":"10.1016\/j.jacr.2025.12.015_bib25","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.2214\/AJR.16.16987","article-title":"Digital breast tomosynthesis: cost-effectiveness of using private and Medicare insurance in community-based health care facilities","volume":"208","author":"Hunter","year":"2017","journal-title":"AJR Am J Roentgenol"},{"key":"10.1016\/j.jacr.2025.12.015_bib26","author":"Stempniak"},{"key":"10.1016\/j.jacr.2025.12.015_bib27","author":"Klyman"},{"key":"10.1016\/j.jacr.2025.12.015_bib28","author":"Rad"},{"key":"10.1016\/j.jacr.2025.12.015_bib30","series-title":"AI driven screening mammography outreach program improves 15-month compliance and reduces the gap for underserved populations","author":"Malav","year":"2024"},{"key":"10.1016\/j.jacr.2025.12.015_bib31","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1016\/j.crad.2021.07.012","article-title":"Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital","volume":"76","author":"Martins Jarnalo","year":"2021","journal-title":"Clin Radiol"},{"key":"10.1016\/j.jacr.2025.12.015_bib33","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s12874-024-02440-x","article-title":"Methodological challenges using routine clinical care data for real-world evidence: a rapid review utilizing a systematic literature search and focus group discussion","volume":"25","author":"Pfaffenlehner","year":"2025","journal-title":"BMC Med Res Methodol"},{"key":"10.1016\/j.jacr.2025.12.015_bib34","doi-asserted-by":"crossref","DOI":"10.1002\/sim.70151","article-title":"Adjusting for selection bias due to missing data in electronic health records-based research by blending multiple imputation and inverse probability weighting","volume":"44","author":"Thaweethai","year":"2025","journal-title":"Stat Med"},{"key":"10.1016\/j.jacr.2025.12.015_bib35","series-title":"Multistage AI-driven workflow improves general radiologist screening mammography performance to the level of fellowship-trained breast imagers: real-world evidence in >500,000 patients","author":"McCabe","year":"2025"}],"container-title":["Journal of the American College of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1546144025007306?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1546144025007306?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T04:17:18Z","timestamp":1778818638000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1546144025007306"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":19,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["S1546144025007306"],"URL":"https:\/\/doi.org\/10.1016\/j.jacr.2025.12.015","relation":{},"ISSN":["1546-1440"],"issn-type":[{"value":"1546-1440","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Learning Accelerator Framework: Scalable Clinical Artificial Intelligence Development and Delivery","name":"articletitle","label":"Article Title"},{"value":"Journal of the American College of Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jacr.2025.12.015","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 Inc. on behalf of American College of Radiology.","name":"copyright","label":"Copyright"}]}}