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Amin Kamaleddin

University of Toronto

35 St George Street

Toronto, M5S1A4

Canada

  • University of Toronto

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Scholarly Papers (1)

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Too Agreeable to Be Accurate? Sycophancy and Diagnostic Instability of Large Language Models in Medical Diagnosis

Number of pages: 21 Posted: 11 May 2026
Christoffer Dharma, Konrad Samsel, Aseel Bahakeen, Kynthia Ravikumar, Venkat Bhat, Amin Kamaleddin and Zahra Shakeri Hossein Abad
McMaster University - Department of Medicine, University of Toronto, University of Toronto, Imperial College London, University of Toronto, University of Toronto and University of Pittsburgh - Department of Biomedical Informatics
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Abstract:

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Artificial intelligence, Large Language Models, medical diagnosis, Clinical decision support, Sycophancy