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中华危重症医学杂志(电子版) ›› 2024, Vol. 17 ›› Issue (03) : 236 -240. doi: 10.3877/cma.j.issn.1674-6880.2024.03.010

综述

深度学习算法在急性缺血性脑卒中后出血转化预测中的应用进展
陈金花1, 李婷2, 姚梅琪1, 马雅英1,(), 吴肖飞1   
  1. 1. 310009 杭州,浙江大学医学院附属第二医院护理部
    2. 313000 浙江湖州,湖州师范学院护理学院
  • 收稿日期:2024-03-20 出版日期:2024-06-30
  • 通信作者: 马雅英
  • 基金资助:
    浙江省医药卫生科技计划项目(2022ZH005、2022KY803)
  • Received:2024-03-20 Published:2024-06-30
引用本文:

陈金花, 李婷, 姚梅琪, 马雅英, 吴肖飞. 深度学习算法在急性缺血性脑卒中后出血转化预测中的应用进展[J]. 中华危重症医学杂志(电子版), 2024, 17(03): 236-240.

急性缺血性脑卒中(acute ischemic stroke,AIS)在中国高发,是首位致死致残重大疾患,已成为当今严重影响居民健康的重大公共卫生问题[1-3]。AIS患者发病后短期病死率为9.0% ~ 9.6%,病死/致残率为34.5% ~ 37.1%[4]。其中,出血转化(hemorrhagic transformation,HT)是AIS最严重的并发症[5-6],严重影响再灌注治疗的效果[7],也是大部分卒中幸存者出现神经功能恶化的主要原因[8]。如果要在AIS再灌注治疗后尽快防治以及逆转HT,临床医师需要早期检测HT。因此,早期准确预测HT以及不良预后,对AIS患者的及时救治和病死率的减少具有重要的临床意义。

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