人工智能在普通外科重症预警与决策支持中应用OA
Application of artificial intelligence in early warning and decision support for critically ill patients in general surgery
普通外科重症病人病情复杂、变化迅速,常涉及多器官功能障碍及严重感染等问题,给临床诊疗带来巨大挑战.传统重症评估工具在一定程度上能够反映病人病情严重程度,但多依赖静态指标,难以实现连续动态评估.近年来,随着医疗大数据和人工智能技术的发展,基于机器学习与深度学习算法的智能模型逐渐应用于重症医学领域,在疾病早期识别、风险预测及临床决策支持方面展现出重要价值.人工智能能够整合电子病历、生命体征监测、实验室指标及影像数据,实现对重症病人病情变化的实时分析与预测,从而为临床医师提供更加精准的决策依据.人工智能在普通外科重症病人早期预警、并发症风险预测以及临床决策支持中的应用有良好的前景,但其在临床推广过程中也面临数据质量、模型可解释性及伦理安全等问题.
Critically ill patients in general surgery often present with complex conditions and rapid clinical deterioration,frequently involving severe infection and multiple organ dysfunction.Traditional severity scoring systems can partially reflect disease severity but rely mainly on static indicators and lack dynamic predictive capability.With the development of medical big data and artificial intelligence(AI),machine learning and deep learning-based models have been increasingly applied in critical care medicine.These technologies show great potential in early disease detection,risk prediction,and clinical decision support.By integrating electronic health records,vital signs,laboratory results,and imaging data,AI can continuously analyze patient conditions and provide real-time predictions to assist clinicians in making timely decisions.AI has promising prospects in the application in early warning systems,complication prediction,and decision support for critically ill patients in general surgery.However,current challenges such as data quality,model interpretability,and ethical issues are discussed to provide references for the standardized application of AI in surgical critical care.
金信浩;沈鸿杰;杨穗碧;林玲;章仲恒
浙江大学医学院附属邵逸夫医院重症医学科,浙江 杭州 310016浙江大学医学院附属邵逸夫医院急诊医学科浙江省腹腔感染精准诊疗重点实验室,浙江 杭州 310016浙江大学医学院附属邵逸夫医院急诊医学科浙江省腹腔感染精准诊疗重点实验室,浙江 杭州 310016浙江大学医学院附属邵逸夫医院重症医学科,浙江 杭州 310016浙江大学医学院附属邵逸夫医院急诊医学科浙江省腹腔感染精准诊疗重点实验室,浙江 杭州 310016||绍兴文理学院医学院,浙江绍兴 321036||龙泉产业创新研究院,浙江丽水 323799
医药卫生
人工智能普通外科重症医学早期预警临床决策支持机器学习
artificial intelligencegeneral surgerycritical careearly warningclinical decision supportmachine learning
《中国实用外科杂志》 2026 (5)
638-644,7
新发突发与重大传染病防控国家科技重大专项(No.2025ZD01902501)国家重点研发计划项目(No.2023YFC3603104)国家自然科学基金项目(No.82272180,No.82472243)浙江大学龙泉创新中心项目(No.ZJDXLQCXZCJBGS2024016)浙江省基础公益研究计划 浙江省自然科学基金华东医药联合基金/重大项目(No.LHDMD24H150001)国家中医药管理局科技司-浙江省中医药管理局共建科技计划项目(No.GZY-ZJ-K1-24082)浙江省医药卫生科技计划项目(No.2024KY1099)浙江省科技厅"尖兵领雁"重点研发攻关计划项目(No.2024C03240)北京市自然科学基金项目(No.7252298)吴阶平医学基金会专项研究基金项目(No.320.6750.2024-23-07)中央高校基本科研业务项目(No.226-2025-00024)浙江省疾病预防控制科技计划项目(No.2026JKZ042) National Science and Technology Major Proj-ect for Prevention and Control of Emerging,Sudden and Major Infectious Diseases(No.2025ZD01902501)National Key Re-search and Development Program of China(No.2023YFC3603104)National Natural Science Foundation of China(No.82272180,No.82472243)Longquan Innovation Center Project of Zhejiang University(No.ZJDXLQCXZCJB-GS2024016)Zhejiang Provincial Natural Science Foundation-Huadong Medicine Joint Fund/Major Project under the Zheji-ang Provincial Basic Public Welfare Research Program(No.LHDMD24H150001)Joint Science and Technology Program of the Department of Science and Technology,National Admin-istration of Traditional Chinese Medicine and Zhejiang Provin-cial Administration of Traditional Chinese Medicine(No.GZY-ZJ-K1-24082)Zhejiang Provincial Medical and Health Sci-ence and Technology Program(No.2024KY1099)"Elite &Leading Goose"Key Research and Development Program of Zhejiang Provincial Department of Science and Technology(No.2024C03240)Beijing Natural Science Foundation(No.7252298)Special Research Fund of Wu Jieping Medical Foundation(No.320.6750.2024-23-07)Fundamental Re-search Funds for the Central Universities(No.226-2025-00024)Zhejiang Provincial Science and Technology Program for Disease Prevention and Control(No.2026JKZ042)
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