{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T03:30:28Z","timestamp":1777519828412,"version":"3.51.4"},"reference-count":38,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Wound Journal"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Diabetic foot ulcers (DFUs) are a growing public health problem, paralleling the increasing incidence of diabetes. While prevention is most effective treatment for DFUs, challenge remains on selecting the optimal treatment in cases with DFUs. Health sciences have greatly benefited from the integration of artificial intelligence (AI) applications across various fields. Regarding amputations in DFUs, both literature and clinical practice have mainly focused on strategies to prevent amputation and identify avoidable risk factor. However, there are very limited data on assistive parameters\/tools that can be used to determine the level of amputation. This study investigated how well ChatGPT, with its lately released version 4o, matches the amputation level selection of an experienced team in this field. For this purpose, clinical photographs from patients who underwent amputations due to diabetic foot ulcers between May 2023 and May 2024 were submitted to the ChatGPT\u20104o program. The AI was tasked with recommending an appropriate amputation level based on these clinical photographs. Data from a total of 60 patients were analysed, with a median age of 64.5\u2009years (range: 41\u201391). According to the Wagner Classification, 32 patients (53.3%) had grade 4 ulcers, 16 patients (26.6%) had grade 5 ulcers, 10 patients (16.6%) had grade 3 ulcers and 2 patients (3.3%) had grade 2 ulcers. A one\u2010to\u2010one correspondence between the AI tool's recommended amputation level and the level actually performed was observed in 50 out of 60 cases (83.3%). In the remaining 10 cases, discrepancies were noted, with the AI consistently recommending a more proximal level of amputation than what was performed. The inter\u2010rater agreement analysis between the actual surgeries and the AI tool's recommendations yielded a Cohen's kappa coefficient of 0.808 (SD: 0.055, 95% CI: 0.701\u20130.916), indicating substantial agreement. Relying solely on clinical photographs, ChatGPT\u20104.0 demonstrates decisions that are largely consistent with those of an experienced team in determining the optimal level of amputation for DFUs, with the exception of hindfoot amputations.<\/jats:p>","DOI":"10.1111\/iwj.70055","type":"journal-article","created":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T23:54:20Z","timestamp":1727826860000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Artificial intelligence's suggestions for level of amputation in diabetic foot ulcers are highly correlated with those of clinicians, only with exception of hindfoot amputations"],"prefix":"10.1111","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4887-8467","authenticated-orcid":false,"given":"Merve","family":"Mert","sequence":"first","affiliation":[{"name":"Department of Orthopedics and Traumatology Ege University School of Medicine  Izmir 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