At National Taiwan University (NTU), artificial intelligence is reshaping the entire medical pathway, from how future clinicians learn to how real patients receive care.

Across the NTU ecosystem, from the university’s engineering labs to the wards of its six affiliated hospitals, AI now operates at the intersection of learning, research, and care. It shows what happens when technology enhances human judgment rather than replaces it.

From Laboratory Insight to Clinical Reality

The flagship National Taiwan University Hospital (NTUH), founded in 1895, is Taiwan’s oldest and largest teaching hospital. It stands at the forefront of the country’s precision medicine revolution. Under the leadership of Dr Ming-Shiang Wu, the hospital’s former superintendent, digital transformation began not as a technology project but as a human one.

“Smart medicine must strengthen, not replace, human care,” he said, framing the principle behind NTUH’s early AI adoption.

That vision led to an integrated data ecosystem combining genomic science, electronic health records, and AI models to support real-time clinical decisions. NTUH now applies machine learning in cardiovascular and imaging diagnostics, developed in collaboration with NTU’s engineering teams and NVIDIA. One result, a free AI cardiac disease screening platform, is now used in Taiwan’s national health system.

In 2024, NTUH installed two NVIDIA supercomputers to support large-scale AI development across text, imaging, and genomic data. Its Centre for Intelligent Healthcare is already using generative AI for automated medical coding, pathology report summarisation, and a virtual reality surgical training platform called OpVerse.

These developments show how NTU and NTUH have built institutional AI capacity that directly supports clinical work and education.

A University-Hospital System at Scale

NTU’s leadership in digital health extends across its six teaching hospitals, which form an integrated network for education, research, and clinical innovation.

This structure allows discoveries to move quickly from laboratory to practice, through telemedicine pilots in regional hospitals or AI-assisted imaging models tested at multiple sites.

For educators, this network provides a living classroom where students and residents see how data-driven systems can improve care without diminishing professional responsibility.

Educating the Digital-Native Clinician

For NTU, technology alone cannot transform healthcare. The next generation of clinicians must learn to interpret, question, and ethically apply algorithmic outputs.

The Graduate Program in Precision Health and Intelligent Medicine (PHIM) was created to bridge that gap. Its curriculum combines data science, clinical informatics, and bioethics so that medical students understand both the science and the human stories behind the data.

Within NTU’s College of Medicine, simulation laboratories now replicate clinical environments using AI-assisted diagnostic tools and virtual surgeries. Students learn not only how to use these systems but when to question them, a skill that will define medical professionalism in the age of AI.

Supported by faculty recognised among the world’s Top 2% Scientists, students work alongside researchers producing globally cited work in medical AI.

This approach prepares clinicians who are both data-literate and compassionate, demonstrating how curriculum design can keep pace with rapid technological change while maintaining ethical grounding.

Building a Regional Model for Responsible Innovation

Taiwan’s universal health insurance database, one of the most comprehensive in the world, gives NTU researchers a unique foundation for real-world AI training.

By integrating these data with genomic and lifestyle information, research teams can study disease patterns specific to Asian populations, addressing a long-standing gap in global medical datasets.

The insights developed in Taipei now support collaborations with universities in Japan and Singapore, positioning NTU as a regional leader in ethical and inclusive digital health. For higher education institutions, this demonstrates how national data resources, when governed responsibly, can drive both academic progress and public benefit.

Lessons for Higher Education

NTU’s experience offers lessons that extend beyond medicine:

· Integrate across disciplines: the most transformative outcomes emerge when engineering, computer science, and clinical faculties work together.

· Teach critical collaboration: training students to engage with, not defer to, AI promotes judgment and accountability.

· Connect innovation with ethics: embedding bioethics in technical training builds trust and long-term sustainability.

· Use institutional scale effectively: large networks and datasets have value only when guided by strong governance and human oversight.

For higher education leaders, the message is clear: embedding AI in teaching and research is not a technical upgrade but a cultural shift that requires shared vision and interdisciplinary fluency.

Beyond the Buzzword

At NTU, artificial intelligence is not a slogan or a laboratory exercise. It is a method that strengthens clinical judgment, advances education, and expands human capability.

By linking bedside experience with algorithmic intelligence, National Taiwan University is showing how technology can help heal while keeping the essence of medicine deeply human.