Artificial intelligence foundation models in healthcare: A Malaysian perspective
Published in Medical Journal of Malaysia, 2026
Shen-Han Lee 1, Irfan Mohamad 1,2,*
1 Department of Otorhinolaryngology, Head and Neck Surgery, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia
2 Hospital Pakar Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan, Malaysia
* Corresponding author: irfankb@usm.my
One of the most revolutionary breakthroughs in modern artificial intelligence research over the past decade has been the introduction of foundation models - deep learning models trained on extensive datasets that can be adapted to tackle a wide range of downstream tasks. The rise of foundation models has significantly accelerated the adoption of AI in healthcare where there is increasing digitalization, enabling the integration of medical imaging, clinical notes, and genomic data to provide a more holistic understanding of patient health and supporting personalized interventions. In this Editorial, we will explore how foundation models are catalysing insights in precision health and offer our perspective of how foundation models can be integrated into the Malaysian healthcare system. In addition, we will also highlight some of the issues concerning governance, ethical, regulatory and policy challenges of implementing these foundation models in the Malaysia.
Keywords: Artificial Intelligence; Foundation Models; Large Language Models; Healthcare; Malaysia.
Link: Medical Journal of Malaysia
PMID: 41617499
Recommended citation: Lee SH, Mohamad I. (2026). "Artificial intelligence foundation models in healthcare: A Malaysian perspective." Medical Journal of Malaysia. 81(1):1-5.
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