评估大型语言模型在预测重症监护病房入院需求方面的有效性
Engin İhsan Turan1, Abdurrahman Engin Baydemir2, Zehra Polat Turan3
1Department of Anesthesiology, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Turkey.
Journal of critical care
|January 24, 2026
概括
在预测重症监护室 (ICU) 入院需求方面,ChatGPT AI显著优于Gemini,显示出更高的准确性和可靠性. 这一进步有助于对重症患者及时进行干预,并可能降低死亡率.
科学领域:
- 临床信息学 临床信息学
- 医疗保健中的人工智能
- 关键护理医学 关键护理医学
背景情况:
- 及时进入重症监护室 (ICU) 对降低重症患者的死亡率至关重要.
- 迟到的ICU转移与患者死亡率的增加有关,因此需要有效的预测系统.
- 人工智能 (AI) 提供了改善临床决策在重症监护机构的潜力.
研究的目的:
- 评估ChatGPT和Gemini AI模型在预测需要ICU入院的有效性.
- 为了比较ChatGPT和双子座的预测性能与麻醉科医生做出的临床决定.
主要方法:
- 从2020年1月到2024年6月,对8043起ICU咨询病例进行了回顾性分析.
- 包括临床参数:药物使用,咨询细节,心电图,成像,并发症和实验室值.
- 使用ChatGPT和Gemini进行AI模型分析,使用包括精度,卡帕统计和后勤回归在内的性能指标.
主要成果:
- 聊天GPT获得了93.8%的准确率和0.802的卡帕统计数据,表明与临床决策有很大一致.
- 聊天GPT预测与实际临床结果具有高度显著的关联 (p < 0.001).
- 与ChatGPT相比,Gemini的卡帕值较低 (0.396),反映出与ChatGPT相比更适度的协议和一致性.
结论:
- 与Gemini相比,ChatGPT在预测ICU入院需求方面表现出卓越的准确性和可靠性.
- 精确的AI驱动预测有助于早期识别重病患者,以便及时进行干预.
- 未来的研究应该专注于将AI整合到临床工作流程和前性验证中.
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