This project develops a new undergraduate elective within the Biomedical Engineering programme to prepare students for the growing role of AI and data analytics in healthcare. Recognising that future biomedical engineers must operate at the interface of technology, clinical practice, and responsibility, the initiative focuses on delivering clinically grounded and ethically informed AI training.

 

The core outcome is an elective on Data Analytics for Biomedical Engineering, structured around fundamentals, applied case studies, and project-based learning. Students engage directly with clinicians and work on real-world healthcare problems using clinical data from PPUM, ensuring early exposure to the realities of medical environments. All project work is aligned with the Data Safe Haven initiative, providing a secure and governed setting that reinforces best practices in data privacy, ethics, and responsible research.

 

A key strength of the project lies in international benchmarking against leading universities, which highlighted the importance of embedding ethics, safety, and governance as core elements of any AI-in-Medicine curriculum. These considerations are therefore integrated alongside technical content, ensuring students understand not only how to build AI systems, but also how to deploy them safely and responsibly in healthcare contexts.

 

The elective is designed with strong translational and industry relevance, shaped through focus group discussions with industry partners. Application areas such as prosthetics and rehabilitation engineering provide clear pathways from education to real-world impact, with relevance to national agencies such as PERKESO, which supports physical rehabilitation and workforce re-entry.

 

Overall, this initiative strengthens the biomedical engineering talent pipeline by embedding secure, ethical, and clinically relevant AI training at the undergraduate level, while creating clear links to healthcare practice, industry collaboration, and societal impact.