Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources
Diagnostic and Interventional Radiology, cilt.30, sa.3, ss.163-174, 2024 (SCI-Expanded, Scopus, TRDizin)
- Yayın Türü: Makale / Derleme
- Cilt numarası: 30 Sayı: 3
- Basım Tarihi: 2024
- Doi Numarası: 10.4274/dir.2023.232496
- Dergi Adı: Diagnostic and Interventional Radiology
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.163-174
- Anahtar Kelimeler: Artificial intelligence ChatGPT digital case studies educational videos radiology education
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) plat-forms have long served as a cornerstone in radiology education, offering rich visual content, interactive sessions, and peer-reviewed materials. They excel in teaching intricate concepts and techniques that necessitate visual aids, such as image interpretation and procedural demonstrations. However, Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI)-powered language model, has made its mark in radiology education. It can generate learning assessments, create lesson plans, act as a round-the-clock virtual tutor, enhance critical thinking, translate materials for broader accessibility, summarize vast amounts of information, and provide real-time feed-back for any subject, including radiology. Concerns have arisen regarding ChatGPT’s data accuracy, currency, and potential biases, especially in specialized fields such as radiology. However, the qual-ity, accessibility, and currency of e-learning content can also be imperfect. To enhance the educational journey for radiology residents, the integration of ChatGPT with expert-curated e-learning resources is imperative for ensuring accuracy and reliability and addressing ethical concerns. While AI is unlikely to entirely supplant traditional radiology study methods, the synergistic combination of AI with traditional e-learning can create a holistic educational experience.