Author

Bálint Zsidai

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Review Open access Sep 2026

Select large language models outperform hip preservation experts on consensus-based hip preservation questionnaire.

PURPOSE Artificial intelligence (AI) is increasingly utilized in medical education and clinical contexts, yet few studies compare the performance of large language models (LLMs) to subspecialized experts in providing guideline-based medical information on hip preservation. The purpose of this study was to evaluate the...

Karter Morris, F. Öttl, James A. Pruneski et al. · Knee Surgery, Sports Traumat... · 0 citations

Review Open access Oct 2026

EP4.9 Comparing Artificial Intelligence Performance to Hip Preservation Experts on Consensus-Based Hip Preservation Questionnaire

Evaluating the performance of three AI platforms versus a panel of international hip preservation experts in answering guideline-based questions related to femoroacetabular impingement syndrome, hip dysplasia, and microinstability of the hip shows that the knowledge of AI is rapidly approaching and/or exceeding that of...

Karter Morris, F. Öttl, James A. Pruneski et al. · Journal of Hip Preservation... · 0 citations

Open access Jul 2026

Four general-purpose large language models (ChatGPT-5, Claude 4, Grok 4 and Gemini 2.5) show comparable performance in specialised total knee arthroplasty clinical questions.

Four general-purpose large language models (ChatGPT-5, Claude 4, Grok 4 and Gemini 2.5) demonstrated good overall performance when addressing specialised clinical questions related to total knee arthroplasty derived from the WEMA.

Oriol Pujol, R. Ferrer, Alex Coelho et al. · Knee Surgery, Sports Traumat... · 1 citation