Incorporating AI Tools into Medical Education: Harnessing the Benefits of ChatGPT and Dall-E

Incorporating AI Tools into Medical Education: Harnessing the Benefits of ChatGPT and Dall-E

Authors

DOI:

https://doi.org/10.56741/jnest.v2i02.315

Keywords:

artificial intelligence (AI), medical education, ChatGPT, Dall-E, large language model (LLM)

Abstract

Artificial intelligence (AI) has shown promising potential to transform various fields, including medical education. Recently, the rapid advancement of AI has led to many ``new'' discoveries that caught everyone's attention. Among those discoveries are introduced by OpenAI (e.g., ChatGPT, Dall-E, and the most recent, GPT-4). The integration of AI tools, such as ChatGPT and Dall-E, can offer a new dimension to medical education by creating an interactive and engaging learning experience. In this article, we explore the potential benefits of ChatGPT and Dall-E in medical education and provide practical utilization examples of those tools. For starters, ChatGPT, or in this sense, any other similar large language models, can simulate patient interactions in a safe environment, allowing medical learners to practice their communication skills and diagnosis techniques. Furthermore, it can assist medical students and researchers in reading and writing academic articles by accurately summarizing the key points of a given topic and generating an indistinguishable abstract. In addition, ChatGPT can also create problems for medical assignments and exam practice. In this article, we also discussed ChatGPT's capability to answer standard medical assignment problems. Dall-E, on the other hand, can generate dummy copyright-free and consent-free medical images (e.g., x-ray and electrocardiogram (ECG) graphs), allowing medical learners to practice and enhance their interpretation skills. Incorporating AI-based tools into medical education can provide a new approach to teaching and learning, bridging the gap between theory and practice, and unlocking new avenues for learning and discoveries for both, the students and the instructors. It can also offer a cost-effective solution to simulate real-world scenarios that would otherwise require significant resources and time. In summary, this article concludes that AI-based tools have the potential to revolutionize medical education, empowering medical learners with the skills and knowledge necessary to excel in their field.

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Author Biographies

Muhammad Miftahul Amri, Universitas Ahmad Dahlan, Indonesia

Muhammad Miftahul Amri received his B.S. from the Department of Computer Science and Electronics, Universitas Gadjah Mada Indonesia in 2018, and an M.S. from the Department of Electrical and Computer Engineering, Sungkyunkwan University South Korea in 2021, where he is currently pursuing his Ph.D. In 2022, he received his M.M. and professional engineer degrees from Universitas Terbuka Indonesia and Universitas Muhammadiyah Yogyakarta Indonesia, respectively. In 2021, he joined the faculty at Universitas Ahmad Dahlan Indonesia, where he is currently a lecturer in the Department of Electrical Engineering. His research interests include wireless communication and reconfigurable intelligent surface. He can be contacted by email: muhammad.amri@te.uad.ac.id.

Urfa Khairatun Hisan, Faculty of Medicine, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

Urfa Khairatun Hisan is a lecturer at the Faculty of Medicine, Universitas Ahmad Dahlan, and a graduate student of the Department of Bioethics, Universitas Gadjah Mada. She received the B.Med. and M.D. degrees from the Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia, in 2017 and 2019, respectively. Her research interests include public health and bioethics in medicine. She can be contacted at email: urfa.hisan@med.uad.ac.id.

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Published

2023-04-24

How to Cite

Miftahul Amri, M., & Khairatun Hisan, U. (2023). Incorporating AI Tools into Medical Education: Harnessing the Benefits of ChatGPT and Dall-E. Journal of Novel Engineering Science and Technology, 2(02), 34–39. https://doi.org/10.56741/jnest.v2i02.315

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