{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T09:35:28Z","timestamp":1764668128916,"version":"3.46.0"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Orthop Surg Traumatol"],"DOI":"10.1007\/s00590-025-04592-y","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T09:31:29Z","timestamp":1764667889000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Novel artificial intelligence model predicts the need for reduction of distal radius fractures"],"prefix":"10.1007","volume":"36","author":[{"given":"Jacob","family":"Scioscia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benjamin","family":"Fiedler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Umar","family":"Ghilzai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dion","family":"Birhiray","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey","family":"Hauck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Srikhar","family":"Chilukuri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rohan","family":"Vemu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua","family":"Morrow","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenzo","family":"Deveza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"issue":"2","key":"4592_CR1","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.ocl.2017.12.001","volume":"49","author":"BM Mauck","year":"2018","unstructured":"Mauck BM, Swigler CW (2018) Evidence-based review of distal radius fractures. Orthop Clin North Am 49(2):211\u2013222. https:\/\/doi.org\/10.1016\/j.ocl.2017.12.001","journal-title":"Orthop Clin North Am"},{"issue":"6","key":"4592_CR2","doi-asserted-by":"publisher","first-page":"e0000278","DOI":"10.1371\/journal.pdig.0000278","volume":"2","author":"LH Nazer","year":"2023","unstructured":"Nazer LH, Zatarah R, Waldrip S et al (2023) Bias in artificial intelligence algorithms and recommendations for mitigation. PLOS Digit Health 2(6):e0000278. https:\/\/doi.org\/10.1371\/journal.pdig.0000278","journal-title":"PLOS Digit Health"},{"issue":"1","key":"4592_CR3","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s10278-021-00519-1","volume":"35","author":"T Suzuki","year":"2022","unstructured":"Suzuki T, Maki S, Yamazaki T et al (2022) Detecting distal radial fractures from wrist radiographs using a deep convolutional neural network with an accuracy comparable to hand orthopedic surgeons. J Digit Imaging 35(1):39\u201346. https:\/\/doi.org\/10.1007\/s10278-021-00519-1","journal-title":"J Digit Imaging"},{"issue":"1","key":"4592_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-023-00913-9","volume":"6","author":"MD Abr\u00e0moff","year":"2023","unstructured":"Abr\u00e0moff MD, Tarver ME, Loyo-Berrios N et al (2023) Considerations for addressing bias in artificial intelligence for health equity. NPJ Digit Med 6(1):1\u20137. https:\/\/doi.org\/10.1038\/s41746-023-00913-9","journal-title":"NPJ Digit Med"},{"issue":"3","key":"4592_CR5","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1177\/15589447221124248","volume":"19","author":"SA Dhanjani","year":"2024","unstructured":"Dhanjani SA, Gomez G, Rogers D, LaPorte D (2024) Are there Racial and ethnic disparities in management and outcomes of surgically treated distal radius fractures? Hand (N Y) 19(3):471\u2013480. https:\/\/doi.org\/10.1177\/15589447221124248","journal-title":"Hand (N Y)"},{"key":"4592_CR6","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1146\/annurev-publhealth-052620-103528","volume":"43","author":"MB Vela","year":"2022","unstructured":"Vela MB, Erondu AI, Smith NA, Peek ME, Woodruff JN, Chin MH (2022) Eliminating explicit and implicit biases in health care: evidence and research needs. Annu Rev Public Health 43:477\u2013501. https:\/\/doi.org\/10.1146\/annurev-publhealth-052620-103528","journal-title":"Annu Rev Public Health"},{"issue":"9","key":"4592_CR7","doi-asserted-by":"publisher","first-page":"6816","DOI":"10.1007\/s00330-021-07811-2","volume":"31","author":"P Tobler","year":"2021","unstructured":"Tobler P, Cyriac J, Kovacs BK et al (2021) AI-based detection and classification of distal radius fractures using low-effort data labeling: evaluation of applicability and effect of training set size. Eur Radiol 31(9):6816\u20136824. https:\/\/doi.org\/10.1007\/s00330-021-07811-2","journal-title":"Eur Radiol"},{"key":"4592_CR8","doi-asserted-by":"publisher","first-page":"108925","DOI":"10.1016\/j.ejrad.2020.108925","volume":"126","author":"C Bl\u00fcthgen","year":"2020","unstructured":"Bl\u00fcthgen C, Becker AS, Vittoria de Martini I, Meier A, Martini K, Frauenfelder T (2020) Detection and localization of distal radius fractures: deep learning system versus radiologists. Eur J Radiol 126:108925. https:\/\/doi.org\/10.1016\/j.ejrad.2020.108925","journal-title":"Eur J Radiol"},{"issue":"9","key":"4592_CR9","doi-asserted-by":"publisher","first-page":"S20","DOI":"10.1016\/j.jhsa.2017.06.049","volume":"42","author":"A Daluiski","year":"2017","unstructured":"Daluiski A, Hotchkiss RN, Hanel D, Chopra S, Lindsey R (2017) A convolutional neural network automatically detects and localizes fractures of the distal radius with greater accuracy than inexperienced clinicians: level 2 evidence. J Hand Surg Am 42(9):S20\u2013S21. https:\/\/doi.org\/10.1016\/j.jhsa.2017.06.049","journal-title":"J Hand Surg Am"},{"issue":"4","key":"4592_CR10","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1080\/17453674.2019.1600125","volume":"90","author":"K Gan","year":"2019","unstructured":"Gan K, Xu D, Lin Y et al (2019) Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments. Acta Orthop 90(4):394\u2013400. https:\/\/doi.org\/10.1080\/17453674.2019.1600125","journal-title":"Acta Orthop"},{"issue":"5","key":"4592_CR11","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/j.crad.2017.11.015","volume":"73","author":"DH Kim","year":"2018","unstructured":"Kim DH, MacKinnon T (2018) Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks. Clin Radiol 73(5):439\u2013445. https:\/\/doi.org\/10.1016\/j.crad.2017.11.015","journal-title":"Clin Radiol"},{"issue":"5","key":"4592_CR12","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.jhsa.2024.01.020","volume":"49","author":"JF Oeding","year":"2024","unstructured":"Oeding JF, Kunze KN, Messer CJ et al (2024) Diagnostic performance of artificial intelligence for detection of scaphoid and distal radius fractures: a systematic review. J Hand Surg Am 49(5):411\u2013422. https:\/\/doi.org\/10.1016\/j.jhsa.2024.01.020","journal-title":"J Hand Surg Am"},{"issue":"5","key":"4592_CR13","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1177\/1558944717735945","volume":"13","author":"JL Truong","year":"2018","unstructured":"Truong JL, Doherty C, Suh N (2018) The effect of socioeconomic factors on outcomes of distal radius fractures: a systematic review. Hand (N Y) 13(5):509\u2013515. https:\/\/doi.org\/10.1177\/1558944717735945","journal-title":"Hand (N Y)"},{"issue":"8","key":"4592_CR14","doi-asserted-by":"publisher","first-page":"e9875","DOI":"10.7759\/cureus.9875","volume":"12","author":"C Ermutlu","year":"2020","unstructured":"Ermutlu C, Mert M, Kovalak E, Kanay E, Obut A, \u00d6zt\u00fcrkmen Y (2020) Management of distal radius fractures: comparison of three methods. Cureus 12(8):e9875. https:\/\/doi.org\/10.7759\/cureus.9875","journal-title":"Cureus"},{"key":"4592_CR15","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1051\/sicotj\/2023018","volume":"9","author":"S Sharma","year":"2023","unstructured":"Sharma S (2023) Artificial intelligence for fracture diagnosis in orthopedic X-rays: current developments and future potential. SICOT J 9:21. https:\/\/doi.org\/10.1051\/sicotj\/2023018","journal-title":"SICOT J"},{"issue":"6","key":"4592_CR16","doi-asserted-by":"publisher","first-page":"3974","DOI":"10.1007\/s00330-022-09349-3","volume":"33","author":"M Cohen","year":"2023","unstructured":"Cohen M, Puntonet J, Sanchez J et al (2023) Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs. Eur Radiol 33(6):3974\u20133983. https:\/\/doi.org\/10.1007\/s00330-022-09349-3","journal-title":"Eur Radiol"},{"issue":"1","key":"4592_CR17","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1186\/s13018-022-03408-7","volume":"17","author":"Y Cha","year":"2022","unstructured":"Cha Y, Kim JT, Park CH, Kim JW, Lee SY, Yoo JI (2022) Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review. J Orthop Surg Res 17(1):520. https:\/\/doi.org\/10.1186\/s13018-022-03408-7","journal-title":"J Orthop Surg Res"},{"issue":"2","key":"4592_CR18","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.jhsg.2022.11.007","volume":"5","author":"S Franovic","year":"2023","unstructured":"Franovic S, Pietroski AD, Druskovich K et al (2023) A cost-effectiveness analysis of the various treatment options for distal radius fractures. J Hand Surg Glob Online 5(2):169\u2013177. https:\/\/doi.org\/10.1016\/j.jhsg.2022.11.007","journal-title":"J Hand Surg Glob Online"},{"issue":"1","key":"4592_CR19","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1186\/s13018-021-02845-0","volume":"16","author":"K Oka","year":"2021","unstructured":"Oka K, Shiode R, Yoshii Y, Tanaka H, Iwahashi T, Murase T (2021) Artificial intelligence to diagnose distal radius fracture using biplane plain X-rays. J Orthop Surg Res 16(1):694. https:\/\/doi.org\/10.1186\/s13018-021-02845-0","journal-title":"J Orthop Surg Res"},{"issue":"1suppl","key":"4592_CR20","doi-asserted-by":"publisher","first-page":"95S","DOI":"10.1177\/15589447221075669","volume":"17","author":"R Rahman","year":"2022","unstructured":"Rahman R, Xu AL, Dhanjani SA et al (2022) Does time to imaging and surgery for distal radius fractures vary based on geographic socioeconomic disadvantage? Hand (N Y) 17(1suppl):95S\u2013102S. https:\/\/doi.org\/10.1177\/15589447221075669","journal-title":"Hand (N Y)"},{"issue":"8","key":"4592_CR21","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1302\/2046-3758.128.BJR-2023-0199","volume":"12","author":"ND Clement","year":"2023","unstructured":"Clement ND, Simpson AHRW (2023) Artificial intelligence in orthopaedics. Bone Joint Res 12(8):494\u2013496. https:\/\/doi.org\/10.1302\/2046-3758.128.BJR-2023-0199","journal-title":"Bone Joint Res"},{"issue":"5","key":"4592_CR22","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/j.jhsa.2022.12.018","volume":"48","author":"S Khan","year":"2023","unstructured":"Khan S, Persitz J, Shrouder-Henry J, Khan M, Chan A, Paul R (2023) Effect of time-to-surgery on distal radius fracture outcomes: a systematic review. J Hand Surg Am 48(5):435\u2013443. https:\/\/doi.org\/10.1016\/j.jhsa.2022.12.018","journal-title":"J Hand Surg Am"},{"issue":"7","key":"4592_CR23","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1302\/2046-3758.127.BJR-2023-0111.R1","volume":"12","author":"AB Lisacek-Kiosoglous","year":"2023","unstructured":"Lisacek-Kiosoglous AB, Powling AS, Fontalis A, Gabr A, Mazomenos E, Haddad FS (2023) Artificial intelligence in orthopaedic surgery. Bone Joint Res 12(7):447\u2013454. https:\/\/doi.org\/10.1302\/2046-3758.127.BJR-2023-0111.R1","journal-title":"Bone Joint Res"},{"issue":"2","key":"4592_CR24","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.jht.2016.03.003","volume":"29","author":"NJ MacIntyre","year":"2016","unstructured":"MacIntyre NJ, Dewan N (2016) Epidemiology of distal radius fractures and factors predicting risk and prognosis. J Hand Ther 29(2):136\u2013145. https:\/\/doi.org\/10.1016\/j.jht.2016.03.003","journal-title":"J Hand Ther"}],"container-title":["European Journal of Orthopaedic Surgery &amp; Traumatology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00590-025-04592-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00590-025-04592-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00590-025-04592-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T09:31:30Z","timestamp":1764667890000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00590-025-04592-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,2]]},"references-count":24,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["4592"],"URL":"https:\/\/doi.org\/10.1007\/s00590-025-04592-y","relation":{},"ISSN":["1432-1068"],"issn-type":[{"value":"1432-1068","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,2]]},"assertion":[{"value":"24 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Each author certifies that he or she has no commercial associations (e.g. consultancies, stock ownership, equity interest, patent\/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article. We have no conflicts to disclose, and no funding was obtained for this study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"31"}}