{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:50:17Z","timestamp":1747216217902,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685540"}],"license":[{"start":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T00:00:00Z","timestamp":1732233600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,22]]},"abstract":"<jats:p>Proximal humeral fractures are among the most common fractures seen in emergency departments. Accurately diagnosing and selecting the most appropriate treatment for these fractures can be challenging, and consultation with a senior orthopedic surgeon can be time-consuming for both the patient and the emergency unit. We developed a machine learning model for predicting the type of treatment based on injury radiographic images. The model distinguishes between nonoperative and operative treatment options, achieving an accuracy of 86% and an interobserver reliability (kappa) of 0.722 for test-dataset, which is more than the interobserver agreement between shoulder surgeons. This model has the potential to serve as a therapeutic decision support system for the practitioners in the emergency departments to expedite treatment decisions and to reduce patients\u2019 waiting time.<\/jats:p>","DOI":"10.3233\/shti241080","type":"book-chapter","created":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T11:36:56Z","timestamp":1732275416000},"source":"Crossref","is-referenced-by-count":0,"title":["Using Deep Learning to Suggest Treatment for Proximal Humerus Fractures"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6990-2780","authenticated-orcid":false,"given":"Mohammadreza","family":"Azarpira","sequence":"first","affiliation":[{"name":"Centre Hospitalier Intercommunal de Meulan-Les-Mureaux, Yvelines, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ihssen","family":"Belhadj","sequence":"additional","affiliation":[{"name":"Centre Hospitalier Intercommunal de Meulan-Les-Mureaux, Yvelines, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Khodja","sequence":"additional","affiliation":[{"name":"Centre Hospitalier Intercommunal de Meulan-Les-Mureaux, Yvelines, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Collaboration across Disciplines for the Health of People, Animals and Ecosystems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI241080","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T11:36:56Z","timestamp":1732275416000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI241080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,22]]},"ISBN":["9781643685540"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti241080","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,11,22]]}}}