Weng Onn Chan
Papers
1
Total Citations
2
H-Index
1
About
Weng Onn Chan is a surgical researcher whose work spans the intersection of artificial intelligence and clinical practice, with a particular focus on the safe integration of large language models into medical text generation. His most cited work critically examines OpenAI’s “Deep Research” tool, providing a timely cautionary analysis of its use in producing comprehensive referenced medical content. This paper, published in 2025, has already garnered 2 citations, reflecting the immediate relevance of his contributions to the ongoing dialogue about AI in healthcare. Chan’s research is situated within the vibrant surgical research landscape of Australia and New Zealand, where he is part of a cohort of pre-eminent and prospective surgeons who engage in research alongside their clinical duties. His work underscores the importance of rigorous evaluation before deploying AI tools in medical settings, ensuring that technological advancements do not compromise patient safety or academic integrity. Through his scholarship, Chan contributes to the betterment of surgical sciences by advocating for evidence-based, cautious adoption of emerging technologies.
Research Focus
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Top Papers
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