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| 題 名 | 大型語言模型ChatGPT應用於核子醫學專科醫師考試=The Use of Large Language Models Such as ChatGPT in Nuclear Medicine Board Examination |
|---|---|
| 作 者 | 張思瀚; | 書刊名 | Annals of Nuclear Medicine and Molecular Imaging |
| 卷 期 | 38:1 2025.03[民114.03] |
| 頁 次 | 頁14-21 |
| 分類號 | 312.83 |
| 關鍵詞 | 聊天機器人; 大型語言模型; 核子醫學; 專科醫師考試; Chatbots; ChatGPT; Large language models; Nuclear medicine; Nuclear Medicine Board Examination; |
| 語 文 | 中文(Chinese) |
| DOI | 10.6332/ANMMI.202503_38(1).0002 |
| 中文摘要 | 背景:大型語言模型(Large language models, LLMs) 正在迅速改變醫學和核 子醫學領域。 方法:本實驗從中華民國核醫學會官網收集112 ~ 113 年專科醫師甄審試題 共100 題,以ChatGPT 進行測試。 結果:ChatGPT-4o 正確率為82%, 而ChatGPT-4o1 mini 正確率為69%, 兩者有達統計學的顯著差異(p-value = 0.009322)。GhatGPT-4o 在含有圖片 的題目中,正確率為56.56% (9/14),而只含文字的題目正確率為84.88% (73/86),但兩者並無統計學顯著差異(p-value = 0.1247)。ChatGPT-4o1 mini 在含有圖片的題目中,正確率為50% (7/14),而只含文字的題目正確率為 72.09% (62/86),但兩者亦無統計學顯著差異(p-value = 0.1223)。 結論:本研究顯示LLMs 已對核子醫學科的專業知識有令人驚艷的處理能 力。但醫療從業人員在應用類似技術時,仍需要充份確認其正確性,以避免 誤用。 |
| 英文摘要 | Background: Large language models (LLMs) are rapidly transforming the fields of medicine and nuclear medicine. Methods: In this study, we collected 100 Nuclear Medicine Board Examination questions from the website of the Society of Nuclear Medicine, Taiwan (R.O.C), spanning the years 2023–2024. The questions were tested using ChatGPT. Results: ChatGPT-4o achieved an accuracy rate of 82%, while ChatGPT-4o1 mini achieved 69%, with a statistically significant difference between the two models (p-value = 0.009322). For questions containing images, ChatGPT-4o had an accuracy rate of 56.56% (9/14), while for text-only questions, its accuracy rate was 84.88% (73/86); however, the difference was not statistically significant (p-value = 0.1247). ChatGPT-4o1 mini achieved an accuracy rate of 50% (7/14) for questions containing images and 72.09% (62/86) for text-based questions, with no statistically significant difference (p-value = 0.1223). Conclusions: This study demonstrates that LLMs exhibit remarkable understanding of nuclear medicine knowledge. However, medical professionals must thoroughly verify the accuracy of such technologies to prevent misuse. |
本系統中英文摘要資訊取自各篇刊載內容。