通过人工智能大型语言模型ChatGPT对心脏成像问题的反应的评估
Cynthia L Monroe1, Yasser G Abdelhafez2, Kwame Atsina3
1College of Medicine, California Northstate University, 9700 W Taron Dr, Elk Grove, CA 95757, USA.
Clinical imaging
|May 31, 2024
概括
在回答心脏成像患者教育问题时,ChatGPT-4表现出比ChatGPT-3.5更高的准确性和一致性. 虽然得到了改进,但人工智能反应需要进一步改进,以确保安全的临床使用.
科学领域:
- 医疗教育中的人工智能
- 心脏成像 患者沟通 心脏成像
- 在医疗保健中的自然语言处理.
背景情况:
- 患者教育对于理解心脏成像程序和结果至关重要.
- 像ChatGPT这样的大型语言模型 (LLM) 提供了作为可访问的患者信息资源的潜力.
- 评估人工智能生成的医疗信息的准确性和可靠性至关重要.
研究的目的:
- 评估ChatGPT (版本3.5和4) 在教育患者心脏成像方面的有效性.
- 评估人工智能对心脏成像诊断,模式,指示,报告解释和管理的正确性和一致性.
主要方法:
- 在三个单独的会议中,向ChatGPT-3.5和ChatGPT-4提出了30个关于心脏成像的不同问题.
- 两个心脏病专家和一个心脏放射专家独立评估了答案的正确性和临床准确性.
- 通过基于多数的评分来评估跨会话的响应一致性和整体正确性.
主要成果:
- 聊天GPT-4实现了75%的正确率,超过了ChatGPT-3.5的61%的正确率.
- 与ChatGPT-3.5 (87%) 相比,ChatGPT-4的响应一致性更高 (97%).
- 这两种模型都为71% (ChatGPT-4) 和61% (ChatGPT-3.5) 的问题提供了准确和一致的答案.
结论:
- 在心脏成像患者教育方面,ChatGPT-4表现出比ChatGPT-3.5更好的性能.
- 尽管有所改善,但存在不准确或误导性反应,需要在临床患者教育部署之前进一步开发人工智能模型.
- 目前的人工智能能力需要仔细监督,以确保医疗环境中的患者安全和信息准确性.
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