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多学科的人工智能系统与单一模型的方法对诊断和管理的阴囊和卷囊
Mete Ucdal1, Karya Yurtsever2, Evren Ekingen3
1Department of Internal Medicine, Etimesgut Sehit Sait Ertürk State Hospital, Eryaman, Ankara, Turkey. meteucdal@hacettepe.edu.tr.
BMC gastroenterology
|January 21, 2026
概括
与单个人工智能模型相比,多学科的人工智能系统表现出优越的诊断准确性和对阴囊和阴囊的准则遵守. 这种方法有望改善紧急胃肠道护理中的临床决策支持.
科学领域:
- 医疗人工智能 医疗人工智能
- 胃肠道诊断 胃肠道诊断 胃肠道诊断
- 临床决策支持系统 临床决策支持系统
背景情况:
- 准确的结节和卷积的诊断对于有效的紧急护理和患者的治疗结果至关重要.
- 目前的管理依赖于临床决定,诊断的准确性各不相同.
- 人工智能系统在急性条件下提供了增强诊断能力的潜力.
研究的目的:
- 为了比较多学科人工智能系统的诊断准确度和准则遵守,与单个人工智能模型和人类临床团队进行比较.
- 评估AI在治疗急性胃肠道疾病 (如大和卷) 的表现.
- 评估人工智能驱动的决策与临床实践的速度和一致性.
主要方法:
- 追溯分析234名成年患有阴囊或卷囊的患者 (2018年1月至2024年12月).
- 三种方法的比较: (1) 多学科AI (GPT-4 V,Med-PaLM,BioGPT,LLaMA 4), (2) 单一AI (ChatGPT 5.5.0),以及 (3) 临床团队.
- 关键结果:诊断准确性,决策调整和遵守指南.
主要成果:
- 多学科人工智能实现了94.4%的准确性,超过了ChatGPT (87.2%) 和临床团队.
- 通过多学科系统,对西格体卷积,体卷积手术,骨治疗和ICU分组的更高的准则遵守.
- 多学科人工智能表现出优越的外科决策调整 (92.8%) 和ICU入院预测 (90.6%),决策速度更快 (2.5分钟与ChatGPT的3.2分钟相比,临床医生的15.3分钟).
结论:
- 多学科的人工智能系统在诊断和管理结节和卷发症方面显著优于单一的人工智能模型.
- 特定任务的人工智能集成显示了增强临床支持系统的潜力.
- 在这些AI系统的常规临床实施之前,需要进一步验证.
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