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Assessment of Large Language Models for Enhancing Diabetologist-Developed Personalized Treatment Plans in Complex
Michelle Wang1,2, Madhumita Sushil2, Christopher Y K Williams2
1Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA.
Abstract:
Treatment decisions for type 2 diabetes are complex and multifactorial. This study evaluated the utility of OpenAI's generative pre-trained transformer-4 (GPT-4) large language model in enhancing treatment plans for people with diabetes. The authors assessed GPT-4's ability to extract and critically evaluate diabetologist-developed treatment plans from patients' clinical notes. GPT-4 accurately discerned personalized treatment goals but performed suboptimally when identifying plans that could be further improved and personalized. However, 40% of GPT-4's reasoning and explanations were still considered helpful by experienced academic diabetologists, suggesting a potential broad benefit to less expert physicians, such as those in primary care settings.
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