多模式人工智能聊天机器人的性能在临床瘤病例上进行了评估
David Chen1,2, Ryan S Huang1,2, Jane Jomy1,2
1Radiation Medicine Program, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada.
JAMA network open
|October 23, 2024
概括
多模式人工智能 (AI) 聊天机器人在临床瘤病例中并不比纯文本AI聊天机器人更准确. 需要进一步的研究来提高多式联络AI在瘤诊断中的准确性.
科学领域:
- 人工智能在医学中的应用
- 瘤学 诊断 诊断 瘤学
- 医学聊天机器人技术 医学聊天机器人技术
背景情况:
- 多模式人工智能 (AI) 聊天机器人可以处理图像和文本数据,与单模式 (仅文本) AI 相比,潜在地提高了诊断准确性.
- 在临床瘤学中,多模式AI聊天机器人与单模式AI聊天机器人的比较医疗准确性仍未得到充分研究.
研究的目的:
- 评估多模式和单模式人工智能聊天机器人的准确性,以回答临床瘤病例问题.
- 评估即时工程技术,特别是零射击思维链对聊天机器人的性能的影响.
主要方法:
- 一项横截面研究评估了10个AI聊天机器人 (3个多式,7个单式) 使用来自JAMA网络学习的79个临床瘤病例.
- 医学准确性是使用多选项和自由文本响应进行基准测试的.
- 一个由瘤学专家组成的小组评估了自由文本答复.
主要成果:
- 在多式联络聊天机器人与单式联络聊天机器人之间,没有发现多式联络聊天机器人在准确性方面具有一致的优势.
- 在多选项评估 (高达72.15%) 和自由文本评估 (高达37.97%) 之间,表现最高.
- 多模式聊天机器人的准确性随着涉及多个图像的情况而下降,10个聊天机器人中的9个在自由文本中显示出较低的准确性,而不是多选格式.
结论:
- 在这项研究中,多式人工智能聊天机器人与单式聊天机器人相比,在临床瘤病例中没有表现出更高的医疗准确性.
- 多式联络人工智能需要优化,以有效地整合图像数据,以提高瘤学特定的准确性和可靠性.
- 进一步的研究对于提高AI在瘤学中的临床实用性至关重要.
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