This article presents an innovative approach to addressing the challenges faced by first-year medical students in acquiring and understanding English medical terminology. Recognizing the limitations of traditional and inconsistent online dictionary resources, the Department of Foreign Languages, the Faculty of Fundamental Sciences (FFS) at the University of Medicine and Pharmacy at Ho Chi Minh City (UMP) has developed an AI-powered English-English-Vietnamese medical terminology dictionary. Integrated into the FFS website and powered by ChatGPT and Natural Language Processing (NLP) technologies, this tool provides simplified, contextually accurate definitions tailored to the needs of health science learners. Drawing from authoritative sources and continuously refined through AI, the dictionary supports vocabulary development, academic reading, and international research readiness. Insights from a pilot survey conducted with 235 first-year medical students revealed high demand for a reliable, accessible, and student-friendly medical dictionary. The survey findings highlighted frequent usage of English medical terms, common difficulties in understanding complex definitions, and strong support for an online dictionary with integrated features such as pronunciation, simplified explanations, and mobile accessibility. These results informed the design and implementation of the tool, emphasizing a learner-centered approach and technological integration in medical education. The study underscores the potential of AI to enhance terminology acquisition, promote standardized language use, and modernize digital learning resources in health education. Keywords: AI in education, medical terminology, English for health sciences, ChatGPT, NLP, online medical dictionary, UMP. DOI: 10.7176/JLLL/106-03 Publication date: May 30th 2025
Dao et al. (Wed,) studied this question.