大规模批量伤员检伤分类系统应用研究进展  

Research progress on the application of large-scale batch injury detection and classification system

作　　者：张睿智 罗瑞虹 卢兵 邢佳溢 黎檀实[1] ZHANG Ruizhi;LUO Ruihong;LU Bing;XING Jiayi;LI Tanshi(Department of Emergency Medicine,the First Medical Center of the General Hospital of the People's Liberation Army,Beijing 100039,China)

机构地区：[1]解放军总医院第一医学中心急诊医学科,北京100039 [2]清华大学软件学院,北京100084

出　　处：《中国急救复苏与灾害医学杂志》2024年第9期1241-1245,1260,共6页China Journal of Emergency Resuscitation and Disaster Medicine

基　　金：国家重点研发计划(编号:2023YFF1203805)。

摘　　要：在大规模批量伤员伤亡事件中,现场及院前检伤分类在很大程度上可以在医疗资源有限的前提下降低死亡率。尽管世界各地都存在不同的检伤分类标准,但尚未达成共识。通过对各种检伤方法回顾研究,结合人工智能算法及可穿戴式设备的研究进展,为提高检伤分类效果提供参考。In large-scale casualty incidents,on-site and pre-hospital triage can largely reduce mortality under the premise of limited medical resources.Different triage standards exist around the world,but there is no consensus.This paper reviews various triage detection methods,combines the research progress of artificial intelligence algorithms and wearable devices,in order to provide reference for improving the classification effect of flaw detection.

关 键 词：大规模伤亡事件 批量伤员 检伤分类 

分 类 号：R64[医药卫生—外科学]