<b>Assessment of Large Language Models for Enhancing Diabetologist-Developed Personalized Treatment Plans in Complex Type 2 Diabetes</b>

<p dir="ltr">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.</p><p><br></p><p dir="ltr"><b>Key Points</b></p><p dir="ltr">· GPT-4 has demonstrated potential in retaining complex concepts crucial for developing type 2 diabetes personalized treatment plans. This study evaluated the utility of GPT-4 in enhancing treatment plans for actual patients with diabetes.</p><p dir="ltr">· GPT-4 accurately discerned personalized treatment goals but was suboptimal in identifying diabetologist-developed treatment plans that could be further improved and personalized. Even so, 40% of GPT-4’s reasoning and explanations were considered helpful when evaluated by blinded expert academic diabetologists.</p><p dir="ltr">· These findings suggest the potential of broad benefit of GPT-4 in enhancing treatment plans to less expert physicians, such as those practicing in primary care settings.</p>

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Publication Details

Published
2025-08-20
DOI
https://doi.org/10.2337/figshare.29464577
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Topic Modeling
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article

Assessment of Large Language Models for Enhancing Diabetologist-Developed Personalized Treatment Plans in Complex Type 2 Diabetes

Madhumita Sushil, Victoria Hsiao, Brenda Y. Miao, Atul J. Butte et al.
Topic Modeling
article

Assessment of Large Language Models for Enhancing Diabetologist-Developed Personalized Treatment Plans in Complex Type 2 Diabetes

Madhumita Sushil, Victoria Hsiao, Brenda Y. Miao, Atul J. Butte, Michelle Wang, Christopher Y. K. Williams, Umesh Masharani, Gregory Ku, Aloukika Shah, Suneil K. Koliwad, Sarah Kim
article en

Abstract

<p dir="ltr">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.</p><p><br></p><p dir="ltr"><b>Key Points</b></p><p dir="ltr">· GPT-4 has demonstrated potential in retaining complex concepts crucial for developing type 2 diabetes personalized treatment plans. This study evaluated the utility of GPT-4 in enhancing treatment plans for actual patients with diabetes.</p><p dir="ltr">· GPT-4 accurately discerned personalized treatment goals but was suboptimal in identifying diabetologist-developed treatment plans that could be further improved and personalized. Even so, 40% of GPT-4’s reasoning and explanations were considered helpful when evaluated by blinded expert academic diabetologists.</p><p dir="ltr">· These findings suggest the potential of broad benefit of GPT-4 in enhancing treatment plans to less expert physicians, such as those practicing in primary care settings.</p>

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