Focusing on AI to Lead the Future: TMU Hosts ‘A.I. For ALL’ Forum

Taipei Medical University (TMU) hosted the “A.I. For ALL Forum” on June 19, 2024, focusing on the future of artificial intelligence (AI). The event was jointly organized by the School of Medicine, College of Medical Science and Technology, and the Office of Information Technology. Professor Chi-Chun Lee from National Tsing Hua University’s Department of Electrical Engineering delivered the keynote speech titled “AI in Life: What’s Next?” TMU experts also discussed AI applications in healthcare, education, research, learning, and administration with over 200 participants.​

Professor Lee highlighted AI’s potential to accelerate complex services, extend service boundaries, and uncover innovative insights. He provided examples of AI applications in smart hospitals, integrating AI, IoT, and 5G networks to enhance patient experiences, streamline operations, and reduce costs. In education, he discussed the concept of smart campuses utilizing big data, IoT, AI, and cloud technologies to improve teaching, management, and administration, enabling learning beyond traditional classrooms.​

Dean Chun-Hung Kuo of TMU’s College of Biomedical Engineering shared insights on “AI in Healthcare,” noting that TMU has established seven AI-related medical startups. Future efforts will focus on strengthening infrastructure, integrating advanced technologies, optimizing clinical workflows, and promoting value-based healthcare to develop TMU’s GenAI models.​

Associate Professor Ching-Wen Shih from the Graduate Institute of Cancer Biology and Drug Discovery discussed “AI in Teaching,” covering current applications like learning management systems that analyze student attendance and performance. He envisioned future developments such as intelligent tutoring systems, speech recognition, personalized learning designs, virtual teaching assistants, and immersive learning environments using VR and AR technologies.​

Professors Kai-Cheng Hsu and Hsuan-Chia Yang addressed “Research with AI,” focusing on AI-driven drug development that can significantly reduce time and costs. They emphasized the importance of rich experimental data, cultivating AI talent, and fostering interdisciplinary collaboration to create valuable industry products and services.​

Professor Tzu-Hao Chang from the Graduate Institute of Biomedical Informatics discussed “Learning and Administration with AI,” clarifying that AI replaces tasks, not professions, starting with those lacking tacit knowledge. He highlighted AI applications in learning, such as data management, real-time Q&A, data analysis, and language assistance, and in administration, including document processing, data analysis, report generation, and meeting summaries.​

President Max Wu concluded by emphasizing that “AI For ALL” is about process reengineering. He noted that AI in teaching can shorten course durations, allowing more time for discussion and interaction. The focus should be on integrating AI into daily practices across healthcare, education, research, learning, and administration to enhance TMU’s digital resilience and competitiveness.