Evolution of a Large Language Model for Preoperative Assessment Based on the Japanese Circulation Society 2022 Guideline on Perioperative Cardiovascular Assessment and Management for Non-Cardiac Surgery.

Takahiro Kamihara, Masanori Tabuchi, Takuya Omura, Yumi Suzuki, Tsukasa Aritake,Akihiro Hirashiki,Manabu Kokubo,Atsuya Shimizu

Circulation reports(2024)

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摘要
Background: The Japanese Circulation Society 2022 Guideline on Perioperative Cardiovascular Assessment and Management for Non-Cardiac Surgery standardizes preoperative cardiovascular assessments. The present study investigated the efficacy of a large language model (LLM) in providing accurate responses meeting the JCS 2022 Guideline. Methods and Results: Data on consultation requests, physicians' cardiovascular records, and patients' response content were analyzed. Virtual scenarios were created using real-world clinical data, and a LLM was then consulted for such scenarios. Conclusions: Google BARD could accurately provide responses in accordance with the JCS 2022 Guideline in low-risk cases. Google Gemini has significantly improved its accuracy in intermediate- and high-risk cases.
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