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dc.contributor.authorGürses, Ömer Alperen
dc.date.accessioned2025-04-17T07:22:55Z
dc.date.available2025-04-17T07:22:55Z
dc.date.issued2025en_US
dc.date.submitted2025
dc.identifier.citationÖmer Alperen Gürses, Yapay Zeka Büyük Dil Modellerinin Diz Osteoartriti Fizyoterapi Ve Rehabilitasyonundaki Kullanılabilirliğinin İncelenmesi (Doktora Tezi, Kırşehir Ahi Evran Üniversitesi, 2025.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12513/7250
dc.description.abstractThis study aims to examine the potential usability of artificial intelligence large language models (LLMs) in knee osteoarthritis (OA) physiotherapy and rehabilitation. Forty knee osteoarthritis patients were included in the study. This study compared physiotherapy programs for knee OA developed by three experienced physiotherapists "program recommended by physiotherapists (PRP)" and those generated by the LLMs ChatGPT-4 and Gemini Advanced. Forty patients were assessed using OARSI-recommended criteria. Rehabilitation programs were designed based on this data, with PRP programs developed through collaboration among the physiotherapists and individualized programs generated by each LLMs. The effectiveness of these programs was evaluated by examining the alignment between programs, using chi-square tests to determine statistical significance at p < 0.05. ChatGPT-4o and Gemini Advanced recommended ultrasound more frequently than PRP in Phase 1 (p<0.001), while PRP emphasized hip mobilization exercises (p<0.001), hip abduction, and hamstring curls (p<0.001, p<0.05). Phase 2 highlighted PRP favoring TENS, and hip stabilization exercises over ChatGPT-4o and Gemini Advanced (p<0.001). In Phase 3, ChatGPT-4o recommended NMES and RUS currents significantly more (p<0.001), while dynamic balance exercises aligned with PRP but were lower in Gemini Advanced (p<0.001). xv ChatGPT-4o exhibited discrepancies with the Consensus in 13 of the 50 parameters, achieving an agreement rate of 74%. In contrast, Gemini Advanced showed discrepancies in 15 parameters, corresponding to a 70% agreement rate. The average percentages of recommendations for each parameter were calculated as follows: In Phase 1, recommendations were 82.5% for PRP, 75% for ChatGPT4o, and 76.11% for Gemini Advanced; in Phase 2, 90.66% for PRP, 72.24% for ChatGPT4o, and 62.5% for Gemini Advanced; and in Phase 3, 82.15% for PRP, 84.42% for ChatGPT4o, and 68.08% for Gemini Advanced. This study highlights ChatGPT-4o and Gemini Advanced's potential to assist clinicians in creating patient-specific knee OA rehabilitation programs, while emphasizing the need for improved guideline adherence and data accuracy for full clinical integration. February 2025, 84 pages.en_US
dc.language.isoturen_US
dc.publisherKırşehir Ahi Evran Üniversitesi - Sağlık Bilimleri Enstitüsüen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial İntelligenceen_US
dc.subjectLarge Language Modelsen_US
dc.subjectPhysiotherapyen_US
dc.subjectRehabilitation Programen_US
dc.subjectKnee Osteoarthritisen_US
dc.titleYapay Zeka Büyük Dil Modellerinin Diz Osteoartriti Fizyoterapi Ve Rehabilitasyonundaki Kullanılabilirliğinin İncelenmesien_US
dc.typedoctoralThesisen_US
dc.contributor.departmentSağlık Bilimleri Enstitüsüen_US
dc.relation.publicationcategoryTezen_US


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