在GPT聊天机器人中评估BCID2解释和管理的思维链提示:人工智能与人类专家相比如何?
Daniel M Tassone1,2, Matthew M Hitchcock1,3, Connor J Rossier4
1Division of Infectious Diseases, Department of Medicine, Central Virginia VA Health Care System, Richmond, VA, USA.
概括
GPT-4聊天机器人显示出有助于抗菌药物管理的潜力,但尚未替代专家传染病 (ID) 医生监督. 该研究发现,与人类专家相比,聊天机器人的不充分建议率更高.
科学领域:
- 传染性疾病 传染性疾病
- 医疗信息学 医疗信息学
- 抗微生物药物管理委员会
背景情况:
- 像BIOFIRE血液培养识别2 (BCID2) 面板这样的快速分子诊断可以加速血液感染中的病原体识别.
- 解释BCID2结果和优化抗菌疗法需要传染病 (ID) 专业知识,这往往是有限的.
- 由GPT驱动的聊天机器人提供了一个潜在的解决方案,通过协助非专业提供者来支持抗菌管理计划 (ASP).
研究的目的:
- 评估GPT-4驱动聊天机器人在解释BCID2结果和提供治疗建议方面的性能.
- 将聊天机器人的建议与未来的审计和ASP的反干预进行比较.
- 评估人工智能驱动的建议在管理细菌病的准确性和安全性.
主要方法:
- 一项前性观察性研究,涉及VA医疗中心连续43例细菌病例.
- 使用GPT-4聊天机器人,具有思维链提示和外部知识集成,用于生成建议.
- 独立的传染病医生评估了聊天机器人和ASP在解释,源控制,抗生素治疗和诊断方面的建议.
主要成果:
- 与ASP干预 (4%,p=0.047) 相比,GPT-4聊天机器人显示有害或不充分的建议率 (13%) 显著更高.
- 有害的抗生素治疗建议在聊天机器人中更频繁 (高达10%,p<0.05).
- 聊天机器人在BCID2解释中实现了100%的准确性,但提供了更不充分的源控制建议 (10%对2%的ASP,p=0.022).
结论:
- 采用GPT驱动的聊天机器人显示出作为抗菌药物管理的补充工具的潜力.
- 当前的人工智能聊天机器人应该补充,而不是取代人类传染病专业知识在管理血液感染方面的关键作用.
- 需要进一步开发和验证,以确保AI在临床决策支持中的安全性和有效性.
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