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用自然语言处理预测急诊室的败血症诊断:回顾性队列研究

Felix Brann1, Nicholas William Sterling1, Stephanie O Frisch1

  • 1Vital Software, Inc, Claymont, DE, United States.

JMIR AI
|June 14, 2024
PubMed
概括

机器学习使用护理笔记和临床数据准确地预测急诊部 (ED) 毒症的分类. 这种工具可以促进早期检测和干预败血症,改善患者的治疗结果.

关键词:
紧急情况部门的急救部门.机器学习是机器学习.自然语言处理自然语言处理.已经有了血症.选分类是为了分类.

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