大型语言模型ChatGPT-4omni能预测成年状态患者的结果吗?
Simon A Amacher1,2, Sira M Baumann1, Sebastian Berger1
1Clinic for Intensive Care Medicine, Department of Acute Care, University Hospital Basel, Basel, Switzerland.
Epilepsia
|December 26, 2024
概括
聊天生成预训练变压器-4omni (ChatGPT-4o) 显示状态患者的预测结果不可靠. 临床医生应避免在这个关键患者群体中使用ChatGPT-4o进行预后.
科学领域:
- 神经学 神经学
- 人工智能在医学中的应用
- 临床决策支持 临床决策支持
背景情况:
- 大型语言模型 (LLM) 越来越多地被用于临床应用,包括诊断和决策.
- 状态是一种关键的神经紧急情况,需要准确的预后评估.
研究的目的:
- 评估聊天生成预训练变压器-4omni (ChatGPT-4o) 在预测 status epilepticus患者的预后表现.
- 为了比较ChatGPT-4o的预测准确度与已建立的状态发症严重性得分 (STESS).
主要方法:
- 成年患者被诊断患有 status epilepticus 的回顾性单中心队列研究 (2005年1月 - 2022年12月).
- 主要结局:存活到出院. 二次结局:恢复病前的神经功能.
- 评估了ChatGPT-4o (灵敏度,特异性,尤登指数) 的性能,并与STESS进行了比较.
主要成果:
- 聊天GPT-4o表现出75.8%的灵敏度和36.6%的特异性,用于预测存活率 (尤登指数0.12).
- 为了预测病前神经功能恢复,ChatGPT-4o显示了43.2%的灵敏度和74.7%的特异性 (尤登指数0.12).
- 在ChatGPT-4o和STESS之间的预后性能中没有发现显著差异;进一步提示并没有提高准确性.
结论:
- 聊天GPT-4o表现出不可靠的预测能力,患者在状态的结果.
- 目前的证据表明,临床医生不应该依赖ChatGPT-4o来预测状态病例的预后.
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