دورية أكاديمية

Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources

التفاصيل البيبلوغرافية
العنوان: Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources
المؤلفون: İsmail Meşe, Ceylan Altıntaş Taşlıçay, Beyza Nur Kuzan, Taha Yusuf Kuzan, Ali Kemal Sivrioğlu
المصدر: Diagnostic and Interventional Radiology, Vol 30, Iss 3, Pp 163-174 (2024)
بيانات النشر: Galenos Publishing House, 2024.
سنة النشر: 2024
المجموعة: LCC:Medical physics. Medical radiology. Nuclear medicine
مصطلحات موضوعية: artificial intelligence, chatgpt, digital case studies, educational videos, radiology education, Medical physics. Medical radiology. Nuclear medicine, R895-920
الوصف: Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) platforms 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 feedback 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 quality, 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1305-3612
Relation: http://www.dirjournal.org/archives/archive-detail/article-preview/educating-the-next-generation-of-radiologists-a-co/63970; https://doaj.org/toc/1305-3612
DOI: 10.4274/dir.2023.232496
URL الوصول: https://doaj.org/article/cf73fa0c1f524efa935b38b877652c7f
رقم الأكسشن: edsdoj.f73fa0c1f524efa935b38b877652c7f
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:13053612
DOI:10.4274/dir.2023.232496