Artificial intelligence is actively transforming healthcare today. From diagnostic tools that surpass human experts to predictive models for personalized treatment, AI is reshaping medical practice. This transformation demands a new generation of professionals skilled in both their disciplines and cross-disciplinary collaboration.

The School of Medicine at The Chinese University of Hong Kong, Shenzhen presents the Interdisciplinary AI in Medicine Course Series. Professor Alice Kwai-Yee Siu, Assistant Dean (Clinical Education), and Professor Jenkin Tsui, Leader of the year 3 curriculum in the Clinical Medicine Programme, spearheaded the development of this three-part curriculum, which gradually expands students' knowledge by exposing them to both theoretical concepts and real-world applications."

All courses welcome any student.

This course series is built upon a time-honored medical training paradigm: "see one" (observational learning), "do one" (hands-on capstone projects), and "teach one" (peer-to-peer knowledge sharing). We specifically designed these courses for motivated medical students seeking interdisciplinary exposure. Recognizing the intensive nature of medical studies, we strategically schedule these sessions as evening electives. The response has exceeded all expectations - our initial cohort of 40 students has grown to nearly 80, with strong interest from all academic years. This expanded participation has created an additional benefit: fostering meaningful connections and collaboration across different stages of medical training.

Course 1: AI for the Clinician's Mind

Medical Student Elective 

This course demystifies AI for medical students through practical tools. Participants learn programming fundamentals before exploring machine learning training methods. This foundation enables effective collaboration with computer science experts. We aim to create not AI engineers, but physicians who can intelligently utilize and critically evaluate AI technology.

Clinical Medicine students learning the basics of Python programming.

Course 2: Medicine for the AI Scientific Brain 

AI students often find human biology as mysterious as physicians find algorithms. This course provides the essential medical foundation for developing effective healthcare solutions. Students gain concentrated knowledge of human physiology, disease pathways, and clinical workflows - a crucial understanding often missing in technological innovation.

A clinical medicine lecture on Pyrexia of Unknown Origin at The Second Affiliated Hospital of CUHK-Shenzhen.

Course 3: The AI-Medicine Innovation Lab

AI Capstone Project AI

In 2024 and 2025, this capstone project course has been opened only to medical students. Starting in 2026, however, this capstone course unites medical and AI students in a collaborative environment. Here, theoretical knowledge meets practical application through interdisciplinary teamwork. Students tackle a significant real-world challenge: conceiving and designing an AI-driven solution to a pressing medical issue.

Guided by clinical and AI faculty, students form interdisciplinary teams based on initial proposals. These teams experience the complete innovation lifecycle, from concept to implementation, in this hands-on digital health incubator.

Students teams discuss proposals to approach medical issues with AI solutions using the PICO framework.

A Unified Vision for Healthcare

Healthcare's future lies at the medicine-technology intersection, shaped by young pioneers. The AI in Medicine Series cultivates a shared language between future doctors and AI scientists, ensuring innovation is both technologically advanced and human-centered. This is more than a curriculum - it's a launchpad for healthcare revolutionaries.

Fostering Youth Talent: A senior medical student leads a discussion on using AI as a study aid with first-year students.

培养青年人才：一名医学高年级学生正与大一新生探讨如何将AI作为学习辅助工具。

Distinguishing Features of the AI in Medicine Series at CUHK-Shenzhen

Course 1: AI for the Clinician's Mind

The CMED programme has introduced an optional elective to spark interest in AI. This allows us to engage students who are motivated and passionate through a non-mandatory, free elective.

Course 2: Medicine for the AI Scientific Brain

To facilitate cross-pollination with AI-focused learners, CMED will open an overview course to encourage collaborative research.

Course 3: The AI-Medicine Innovation Lab

Following the 'see one, do one, teach one' model, students will learn how to develop research proposals and presentations. This will build a common skill set for teamwork and approaching AI projects.

"Young people should be at the forefront of global change and innovation. They are agents of change and have the idealism and the courage to shake the foundations of the old order."

— Kofi Annan