Evaluation of ChatGPT-4.5 and DeepSeek-V3-R1 in answering patient-centered questions about orthognathic surgery: a comparative study across two languages

Aim: Patients undergoing orthognathic surgery frequently seek online resources to better understand the procedure, risks, and outcomes. As generative artificial intelligence (AI) models are increasingly integrated into healthcare communication, it is essential to evaluate their ability to deliver accurate, comprehensive, and readable patient information. Methods: This study conducted a comparative assessment of two large language models (LLMs)—ChatGPT-4.5 and DeepSeek-V3-R1—in answering frequently asked orthognathic patient questions, analyzing accuracy, completeness, readability, and quality across English (EN) and Turkish (TR). Twenty-five patient-centered questions categorized into five clinical domains yielded 200 AI-generated responses, independently evaluated by two oral and maxillofacial surgeons (OMFSs) using a multidimensional framework. Statistical analyses included non-parametric tests and inter-rater reliability assessments (Intraclass Correlation Coefficient (ICC), and Cohen’s Kappa). Results: Significant differences emerged across clinical categories in difficulty and accuracy scores (p

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Journal
Northwestern Medical Journal
Published
2025-10-26
DOI
https://doi.org/10.54307/2025.nwmj.220
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Evaluation of ChatGPT-4.5 and DeepSeek-V3-R1 in answering patient-centered questions about orthognathic surgery: a comparative study across two languages

İpek Necla Güldiken, Emrah Dilaver
Northwestern Medical Journal
Artificial Intelligence in Healthcare and Education
article

Evaluation of ChatGPT-4.5 and DeepSeek-V3-R1 in answering patient-centered questions about orthognathic surgery: a comparative study across two languages

İpek Necla Güldiken, Emrah Dilaver
article en

Abstract

Aim: Patients undergoing orthognathic surgery frequently seek online resources to better understand the procedure, risks, and outcomes. As generative artificial intelligence (AI) models are increasingly integrated into healthcare communication, it is essential to evaluate their ability to deliver accurate, comprehensive, and readable patient information. Methods: This study conducted a comparative assessment of two large language models (LLMs)—ChatGPT-4.5 and DeepSeek-V3-R1—in answering frequently asked orthognathic patient questions, analyzing accuracy, completeness, readability, and quality across English (EN) and Turkish (TR). Twenty-five patient-centered questions categorized into five clinical domains yielded 200 AI-generated responses, independently evaluated by two oral and maxillofacial surgeons (OMFSs) using a multidimensional framework. Statistical analyses included non-parametric tests and inter-rater reliability assessments (Intraclass Correlation Coefficient (ICC), and Cohen’s Kappa). Results: Significant differences emerged across clinical categories in difficulty and accuracy scores (p

Northwestern Medical JournalVol. 5(4)
Istinye University (TR)
Openalex Percentile: Top 77%
Artificial Intelligence in Healthcare and Education
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Evaluation of ChatGPT-4.5 and DeepSeek-V3-R1 in answering patient-centered questions about orthognathic surgery: a comparative study across two languages — İpek Necla Güldiken, Emrah Dilaver · Northwestern Medical Journal (2025) | TGRS Research Map | TGRS