智能化麻醉决策支持系统：从多模态数据融合到围术期闭环管理
杜文波 （ 菏泽医学专科学校临床技能实训中心 ）
https://doi.org/10.37155/2661-4766-0803-19Abstract
现代临床麻醉学已超越单纯提供无痛与肌松的范畴，演变为一门涵盖围术期生命功能精准调控、器官保 护与远期预后改善的关键学科。面对患者个体差异性与手术应激反应的复杂性，传统的、依赖固定阈值与麻醉医师个 人经验的反应式管理模式，在预见性、精准性与一致性方面存在显著局限。“智能化麻醉决策支持系统（I-ADSS）” 系统以围术期精准医学与加速康复外科（ERAS）理念为理论基石，深度融合多模态生命体征监测数据、药物动力学/ 药效学模型、电子病历信息及动态超声影像学评估，通过先进的机器学习算法构建从风险评估、实时预警到干预建议 的完整闭环。
Keywords
人工智能；围术期医学；决策支持系统；多模态监测；机器学习；精准麻醉Full Text
PDFReferences
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Arterial Pressure Waveform Analysis[J]. Anesthesiology,
2018, 129(4): 663-674.
[2] Wijnberge M, Geerts BF, Hol L, et al. Effect of
a Machine Learning-Derived Early Warning System for
Intraoperative Hypotension vs Standard Care on Depth and
Duration of Intraoperative Hypotension During Elective
Noncardiac Surgery: The HYPE Randomized Clinical
Trial[J]. JAMA, 2020, 323(11): 1052-1060.
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Publishing time:2026-03-31
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