Research on the path of AI-Driven educational reform of Medical Imaging Diagnostics
CAI A'hui
CHEN Tongjun
Abstract：Medical Imaging Diagnostics,as a crucial core course in medical imaging technology,has seen its traditional teaching methods become increasingly outdated,failing to keep pace with the rapid advancements in the field.Key challenges in the educational process include limited access to imaging resources,a disconnect between teaching and clinical practice,rigid instructional methodologies,and a lack of diverse evaluation and feedback methods.Artificial intelligence(AI)offers new possibilities for enhancing this course by enabling intelligence,personalized learning experience and providing a technical foundation for interactive education.This study explores AI-driven teaching reform in Medical Imaging Diagnostics from three key dimensions:the development of an AI-integrated medical imaging diagnostic teaching platform,the implementation of a human-AI collaborative"dual-teacher classroom"model,and the establishment of a multi-dimensional teaching evaluation and feedback system.Furthermore,it examines critical challenges in practical implementation,including the standardization of medical imaging data,the evolving role of educators,and differences in student adaptability.These insights aim to facilitate the integration of AI in both medical imaging-assisted diagnosis and medical education.
Keywords：Artificial IntelligenceMedical Imaging DiagnosticsTeaching ReformPathway
Publication Date：2025-05-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 185-189 )