Publisher: HKA Publication Date: 2025-09-11

On September 8, Research Fellow Zhang Buyun from the Institute of Digital Economy at Nanchang Hangkong University was invited to Huankui Lecture Hall, delivering a special lecture titled "Artificial Intelligence: Illuminating the Road to Future Medicine" to the students of Huankui Academy.

Starting with the basic concepts and development history of artificial intelligence, Dr. Zhang elaborated on the core technologies of AI and its characteristics of interdisciplinary integration. He emphasized that AI technology has been widely applied in key fields such as medical image analysis, clinical auxiliary diagnosis, drug research and development, and public health management. It not only greatly improves the efficiency and accuracy of medical services, but also injects new impetus into the innovative breakthroughs of modern medicine.

During the lecture, Dr. Zhang further analyzed the profound impacts of artificial intelligence on medical education, clinical diagnosis and treatment, as well as hospital management models. He stressed that AI is driving the transformation of medical education toward personalization and intelligence, reshaping the path of talent cultivation. Meanwhile, relying on data-driven decision-making methods, AI can also optimize medical service processes and enhance the quality and experience of doctor-patient communication.

Teachers and students launched a lively discussion around the topic: "Against the backdrop of AI empowering medicine, what AI skills and applications do we need to master?" Dr. Zhang suggested that future medical talents should solidify their programming foundation, understand the principles of machine learning, and proficiently use AI tools such as medical image recognition and disease prediction modeling, so as to promote the deep integration of artificial intelligence and medical practice.

Currently, artificial intelligence technology is developing rapidly and integrating into medical practice day by day, gradually changing the traditional medical model. Through systematic explanation and case analysis, this lecture expanded the students' understanding of the cutting-edge trends and innovation potential of "AI + Healthcare", and stimulated their continuous attention and learning enthusiasm for this interdisciplinary field. It is expected that the students will continue to maintain exploration and thinking on the road of future medical development, and accumulate more perspectives and capabilities for the arrival of smart healthcare.

Editor: Huang Kehong