Artificial intelligence in medicine

Abstract

In my role as the handling editor for this Artificial Intelligence (AI) in Medicine issue, I have had the privilege and pleasure of curating the articles. With this issue, we hope to raise attention to the clinical utility and potential pitfalls of AI in medicine. The study by Jiang et al.[1] on deep learning models, when applied to small bowel capsule endoscopy, has shown promise in automating image analysis and aiding abnormality detection, potentially improving diagnostic efficiency. In a compelling commentary, novel health system solutions, such as digitisation of emergency medicine, explore opportunities and issues for considerations on how digital health can complement conventional solutions to bring relief to the current crisis in emergency care.[2] Notably, most articles within this issue explore the ethical and social ramifications of AI, emphasising the urgent need for technology to be developed and used responsibly.[3,4,5,6] They offer in-depth examinations of key considerations such as privacy, autonomy, health equity, and practice implications. Reviews delve into the privacy concerns surrounding video-based monitoring in Parkinson’s patients,[3] potential benefits and harms associated with AI in healthcare delivery,[4] and the concept of individualised digital medicine-enabled or N-of-1 medicine.[5] By working together, we ensure that AI technology is ethically supervised from its inception to its implementation in healthcare delivery.[6] Chotirmall et al.[7] encapsulates the key takeaways from the inaugural International Conference on AI in Medicine held in August 2023 and organised by Lee Kong Chian School of Medicine (LKCMedicine), Nanyang Technological University (NTU), Singapore, in partnership with the College of Engineering, NTU, and National Healthcare Group, Singapore. Themed “What’s the Future of AI in Medicine?”,[7] the conference featured discussions on the potential of AI to advance healthcare objectives of enhanced patient experience, improved outcomes, reduced costs, better team well-being, and the promotion of health equity, especially as efforts pivot towards population health.[6] Finally, the rapid advancement of AI in medicine and medical education is happening at a dizzying pace. It is poised to reshape the pedagogy of medical education and residency training. The introduction of ‘AI-assisted’ and ‘AI-integrated’ paradigms in medical education and physician training addresses challenges such as limited faculty, the need for uniformity amidst expanding medical knowledge, and the constraints of traditional linear learning approaches.[8] However, it is essential to approach the integration of AI into medical school curricula with caution, as emphasised by the ‘slowing down when you should’ approach by Kitto et al.[9] The approach ensures the optimisation of AI translation while considering best evidence medical education practices and patient safety concerns.[9] As we navigate the rapidly evolving landscape of AI, it is crucial that we swiftly adapt and equip ourselves to work alongside these machines, ensuring that we maintain our autonomy in the process. Only by coming together and pooling our efforts can we effectively confront the challenges posed by the AI tsunami, lest we risk being swept away. We extend our heartfelt appreciation to our distinguished guest editors from LKCMedicine, NTU — Professor Joseph Sung, Associate Professor Sanjay Haresh Chotirmall and Assistant Professor Wilson Goh — for their invaluable contributions in curating this timely and thought-provoking issue.

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