在麻醉学中推进混合决策模型:人工智能在术后环境中的应用
Gilberto Duarte-Medrano1, Natalia Nuño-Lámbarri2,3, Daniele Salvatore Paternò4
1Anesthesiology Department of Hospital Medica Sur, Mexico City 11510, Mexico.
Healthcare (Basel, Switzerland)
|January 10, 2026
概括
人工智能 (AI) 通过与人类专业知识的整合来增强麻醉学,以改善外科手术期间的护理. 这种混合模型使用人工智能进行风险预测和监测,增强麻醉师的判断力,以获得更安全,更有效的患者结果.
科学领域:
- 麻醉学 麻醉学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 正在彻底改变麻醉学实践.
- 融合人工智能和人类专业知识的混合决策模型正在发展.
- 机器学习,深度学习和大数据分析是人工智能的关键组成部分.
研究的目的:
- 审查人工智能在麻醉学中的发展和实施.
- 在外科外科环境中检查人工智能应用.
- 讨论人工智能整合的挑战和伦理考虑.
主要方法:
- 对人工智能在麻醉学中的历史基础和当前应用的审查.
- 在麻醉治疗中分析机器学习,深度学习和大数据分析.
- 检查AI在风险预测,监测和程序上下文中的作用.
主要成果:
- 人工智能应用包括风险预测,患者教育,记录分析,呼吸道管理,血液动力学监测,麻醉药物输送和疼痛管理.
- 人工智能在区域麻醉,EEG分析麻醉深度和内镜镇静中显示出实用性.
- 教育工具包括智能模拟器和学术生产力辅助工具.
结论:
- 最优的整合模式是一种混合方法,人工智能增强了麻醉师的判断,而不是取代了它.
- 这种模式提高了外科手术期间护理的安全性,精度和效率.
- 算法透明度,验证和人类监督对于以患者为中心的AI集成至关重要.
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