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评估GPT作为放射性决策的辅助:GPT-4与GPT-3.5在乳腺成像试点中
Arya Rao1, John Kim1, Meghana Kamineni1
1Harvard Medical School, Boston, Massachusetts; Medically Engineered Solutions in Healthcare, Innovation in Operations Research Center, Massachusetts General Hospital, Boston, Massachusetts.
像ChatGPT这样的大型语言模型在放射学中显示出临床决策支持的前景,特别是在乳腺癌查和乳腺疼痛方面. 需要进一步的研究来提高准确性,并探索这些AI工具的更多用例.
科学领域:
- 人工智能在医学中的应用
- 放射学决策支持 放射学决定支持
背景情况:
- 大型语言模型 (LLM) 越来越受欢迎,但它们在临床决策支持中的应用,特别是在放射学中,仍然被低估.
- 评估像ChatGPT这样的LLM的有效性,以确定适当的成像服务,对于推进医疗AI至关重要.
研究的目的:
- 评估ChatGPT-3.5和GPT-4在为乳腺癌查和乳腺疼痛提供适当的成像建议方面的能力.
- 将LLM的绩效与既定指导方针进行比较,例如ACR适当性标准.
主要方法:
- 聊天GPT-3.5和GPT-4被提示使用开放式和选择所有适用于乳腺癌查和乳腺疼痛情景的格式.
- 根据ACR适当性标准评估了响应,每次提示进行三次试验以确保可靠性.
主要成果:
- 与ChatGPT-3.5 (88.9%) 相比,ChatGPT-4在乳腺癌查的选择所有适用格式中显示出更高的准确性 (98.4%).
- 对于乳腺疼痛,ChatGPT-4在开放式提示中获得了比ChatGPT-3.5 (1.125/2) 高的平均得分 (1.666/2).
- 在选择所有适用的乳腺疼痛场景中,GPT-4的表现也超过了GPT-3.5 (77.7%与58.3%对比).
结论:
- 像ChatGPT这样的LLM显示了协助放射学决策和优化放射学服务利用的可行性.
- 需要进一步开发和验证,以提高精度,并扩大这些AI工具在放射学中的临床应用.
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