{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T08:05:09Z","timestamp":1790323509160,"version":"4.1.0"},"reference-count":10,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Osteoporosis and Sarcopenia"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.afos.2026.08.004","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T11:37:38Z","timestamp":1788349058000},"page":"1-2","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"S","title":["From detection to action: Transparency, accuracy, and integration for clinical artificial intelligence in musculoskeletal aging"],"prefix":"10.1016","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6735-4861","authenticated-orcid":false,"given":"Ta-Wei","family":"Tai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8948-0294","authenticated-orcid":false,"given":"Dung Van","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.afos.2026.08.004_bib1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.afos.2026.01.002","article-title":"Artificial intelligence-assisted screening reveals high prevalence of osteoporosis in Vietnamese adults using pelvic and hip radiographs","volume":"12","author":"Nguyen","year":"2026","journal-title":"Osteoporos Sarcopenia"},{"key":"10.1016\/j.afos.2026.08.004_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.afos.2026.05.001","article-title":"Deep learning-based quantification of muscle volume and attenuation and their associations with preinjury ambulatory status in patients with hip fractures","author":"Asano","year":"2026","journal-title":"Osteoporos Sarcopenia"},{"key":"10.1016\/j.afos.2026.08.004_bib3","doi-asserted-by":"crossref","DOI":"10.1016\/j.afos.2026.06.001","article-title":"Federated learning for privacy-preserving opportunistic screening of lumbar-spine DXA-defined osteoporotic-level bone mineral density using chest radiographs: a multi-center independent validation study","author":"Lin","year":"2026","journal-title":"Osteoporos Sarcopenia"},{"key":"10.1016\/j.afos.2026.08.004_bib4","doi-asserted-by":"crossref","DOI":"10.1016\/j.afos.2026.08.001","article-title":"From underdiagnosis to scalable screening: applications of artificial intelligence for vertebral compression fracture detection - a systematic review and meta-analysis of diagnostic performance","author":"Chen","year":"2026","journal-title":"Osteoporos Sarcopenia"},{"key":"10.1016\/j.afos.2026.08.004_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.afos.2026.05.003","article-title":"An integrated deep learning and large language model for automated knee osteoarthritis grading and reporting from the Vietnam Osteoporosis Study","author":"Nguyen","year":"2026","journal-title":"Osteoporos Sarcopenia"},{"issue":"11","key":"10.1016\/j.afos.2026.08.004_bib6","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.1093\/jbmr\/zjae131","article-title":"Development and reporting of artificial intelligence in osteoporosis management","volume":"39","author":"Gatineau","year":"2024","journal-title":"J Bone Miner Res"},{"key":"10.1016\/j.afos.2026.08.004_bib7","doi-asserted-by":"crossref","DOI":"10.1007\/s44163-024-00119-2","article-title":"The role of explainability in AI-supported medical decision-making","volume":"4","author":"Gerdes","year":"2024","journal-title":"Discov Artif Intell"},{"key":"10.1016\/j.afos.2026.08.004_bib8","doi-asserted-by":"crossref","DOI":"10.1007\/s00198-026-08067-6","article-title":"Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region","author":"Huang","year":"2026","journal-title":"Osteoporos Int"},{"key":"10.1016\/j.afos.2026.08.004_bib9","doi-asserted-by":"crossref","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"10.1016\/j.afos.2026.08.004_bib10","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.bone.2018.03.018","article-title":"Fracture liaison services improve outcomes of patients with osteoporosis-related fractures: a systematic literature review and meta-analysis","volume":"111","author":"Wu","year":"2018","journal-title":"Bone"}],"container-title":["Osteoporosis and Sarcopenia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405525526000506?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405525526000506?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T07:37:17Z","timestamp":1790321837000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405525526000506"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":10,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["S2405525526000506"],"URL":"https:\/\/doi.org\/10.1016\/j.afos.2026.08.004","relation":{},"ISSN":["2405-5255"],"issn-type":[{"value":"2405-5255","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"From detection to action: Transparency, accuracy, and integration for clinical artificial intelligence in musculoskeletal aging","name":"articletitle","label":"Article Title"},{"value":"Osteoporosis and Sarcopenia","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.afos.2026.08.004","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"simple-article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Korean Society of Osteoporosis. Publishing services by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}