Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Systematic review of ChatGPT accuracy and performance in Iran’s medical licensing exams: A brief report
6
Zitationen
3
Autoren
2024
Jahr
Abstract
ChatGPT has demonstrated significant potential in various aspects of medicine, including its performance on licensing examinations. In this study, we systematically investigated ChatGPT's performance in Iranian medical exams and assessed the quality of the included studies using a previously published assessment checklist. The study found that ChatGPT achieved an accuracy range of 32-72% on basic science exams, 34-68.5% on pre-internship exams, and 32-84% on residency exams. Notably, its performance was generally higher when the input was provided in English compared to Persian. One study reported a 40% accuracy rate on an endodontic board exam. To establish ChatGPT as a supplementary tool in medical education and clinical practice, we suggest that dedicated guidelines and checklists are needed to ensure high-quality and consistent research in this emerging field.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.250 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.109 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.482 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.434 Zit.