对生成人工智能的评估,以响应临床查询关于逐渐减少抗抑郁药物的评估
Maeve Mac Oscar1, Miriam Boland1, Cathal Cadogan1
1School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland.
Research in social & administrative pharmacy : RSAP
|June 27, 2025
概括
生成型人工智能 (AI) 为抗抑郁药逐渐减少的查询提供了相关和安全的答案. 然而,不准确性和不一致性凸显了对医疗保健专业人士指导的持续需求.
科学领域:
- 数字健康数字健康
- 人工智能在医学中的应用
- 药理学 药理学是指药理学的学科.
背景情况:
- 在线论坛对于抗抑郁药逐渐减少的支持至关重要.
- 生成性AI在临床查询响应中的作用正在调查中.
- 评估人工智能在心理健康信息中的表现至关重要.
研究的目的:
- 评估生成人工智能 (AI) 在回答抗抑郁药逐渐减少的临床查询中的表现.
- 评估人工智能产生的答案的相关性,准确性,完整性和清晰性.
- 将AI的反应与既定的临床指南和患者支持需求进行比较.
主要方法:
- 根据研究和论坛,开发了十个抗抑郁药逐渐减少的查询.
- 使用GPT-4模型向ChatGPT提交查询.
- 独立评估回复的相关性,准确性,完整性和清晰度.
主要成果:
- GPT-4的反应是相关的,在大多数情况下都包括安全网 (8/10).
- 总体而言,准确性,完整性和清晰度不那么有利.
- 确定了不准确性,包括不正确的逐渐缩小方法和AI幻觉.
结论:
- 生成型人工智能提供有关抗抑郁药逐渐减少的相关,安全意识的信息.
- 诸如不准确性等性能问题需要持续依赖医疗保健专业人员.
- 对于在临床环境中强大的AI评估工具,需要进一步的研究.
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