The performance of artificial intelligence-based large language models on ophthalmology-related questions in Swedish proficiency test for medicine: ChatGPT-4 omni vs Gemini 1.5 Pro
Yazarlar (6)
Mehmet Cem Sabaner
Kastamonu Üniversitesi, Türkiye
Kastamonu Üniversitesi, Türkiye
Dr. Öğr. Üyesi Arzu Seyhan Karatepe Haşhaş Sahlgrenska Universitetssjukhuset, Türkiye
Kemal Mert Mutibayraktaroğlu South Älvsborg Hospital, Türkiye
Doç. Dr. Zübeyir YOZGAT Kastamonu Üniversitesi, Türkiye
Oliver Niels Klefter Rigshospitalet, Danimarka
Yousif Subhi Rigshospitalet, Danimarka
| Makale Türü |
Özgün Makale
(SCOPUS dergilerinde yayınlanan tam makale)
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| Dergi Adı | Ajo International | ||
| Dergi ISSN | 2950-2535 Scopus Dergi | ||
| Dergi Tarandığı Indeksler | Scopus | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2024 |
| Cilt / Sayı / Sayfa | 1 / 4 / 100070–0 | DOI | 10.1016/j.ajoint.2024.100070 |
| Makale Linki | https://doi.org/10.1016/j.ajoint.2024.100070 | ||
| UAK Araştırma Alanları |
Göz Hastalıkları
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| Özet |
| PurposeTo compare the interpretation and response context of two commonly used artificial intelligence (AI)-based large language model (LLM) platforms to ophthalmology-related multiple choice questions (MCQs) in the Swedish proficiency test for medicine (“kunskapsprov för läkare”) exams.DesignObservational study.MethodsThe questions of a total of 29 exams held between 2016 and 2024 were reviewed. All ophthalmology-related questions were included in this study, and categorized into ophthalmology sections. Questions were asked to ChatGPT-4o and Gemini 1.5 Pro AI-based LLM chatbots in Swedish and English with specific commands. Secondly, all MCQs were asked again without feedback. As the final step, feedback was given for questions that were still answered incorrectly, and all questions were subsequently re-asked.ResultsA total of 134 ophthalmology-related questions out of 4876 MCQs … |
| Anahtar Kelimeler |
| Artificial intelligence | ChatGPT-4 omni | E-learning | Gemini 1.5 Pro | Large language model | Medical education | Ophthalmology |
Science Direct
The performance of artificial intelligence-based large language models on ophthalmology-related questions in Swedish proficiency test for medicine: ChatGPT-4 omni vs Gemini 1.5 Pro
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 16 |
| Google Scholar | 22 |