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AI performance in emergency medicine fellowship examination: comparative analysis of Chatgpt-4o, Gemini 2.0, Claude 3.5, and Deepseek R1 models
1
Zitationen
9
Autoren
2025
Jahr
Abstract
Large language models can achieve high accuracy rates for knowledge and clinical reasoning questions in emergency medicine but show differences in terms of response consistency and hallucination tendency. While these models have significant potential for use in medical education and as clinical decision support systems (CDSS), they need further development to provide reliable, up-to-date, and accurate information.
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Autoren
Institutionen
- Bilkent University(TR)
- University of Health Science(KH)
- Başkent University Hospital(TR)
- Sağlık Bilimleri Üniversitesi(TR)
- Gülhane Askerî Tıp Akademisi(TR)
- Konya Numune Hastanesi(TR)
- Ministry of Health(TR)
- Memorial Ankara Hospital(TR)
- Ankara Numune Eğitim ve Araştırma Hastanesi(TR)
- University of Health Sciences Antigua(AG)
- Etimesgut Asker Hastanesi(TR)
- Aksaray University(TR)
- İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi(TR)
- State Hospital(GB)