摘要
脓毒症是全球医疗面临的巨大挑战,目前存在的问题主要在于诊断的滞后性和治疗的非特异性。机器学习是从数据中生成知识的数据分析和建模技术,它通过预测未来事件为患者提供警报和建议,帮助临床医师获得经验之外的信息,从而辅助临床决策。近年来,机器学习在脓毒症领域的关注度不断升温,在脓毒症临床诊断、精准治疗和预后评估方面取得了一些突破性的进展,有望构建脓毒症诊断和治疗的新体系。本文对相关文章进行回顾,旨在明确机器学习目前在脓毒症诊疗方面的研究进展,为进一步研究提供方向。
As a big challenge of global healthcare,the main problems of sepsis are the delay of diagnosis and non-specificity of treatment.Machine learning is a data analysis and modeling technique that generates knowledge from data,which provides alarms and suggestions by predicting future events to help clinicians get information beyond their experiences and make decisions.Recently,the attention paid to machine learning has been on the rise in the field of sepsis.Some breakthroughs have already been made in the application of clinical diagnosis,precise treatment,prognostic evaluation of sepsis,which is potential to construct a new system for the diagnosis and treatment of sepsis.This paper reviews relevant articles to summarize advances on machine learning in the diagnosis and treatment of sepsis in order to show the direction for further researches.
作者
姜莲莲
谢剑锋
杨毅
Jiang Lianlian;Xie Jianfeng;Yang Yi(Jiangsu Provincial Key Laboratory of Critical Care Medicine,Department of Critical Care Medicine,Zhongda Hospital,School of Medicine,Southeast University,Nanjing 210009,China)
出处
《中华重症医学电子杂志》
CSCD
2021年第3期252-257,共6页
Chinese Journal Of Critical Care & Intensive Care Medicine(Electronic Edition)
基金
江苏省社会发展专项(BE2018743)
国家自然科学基金面上项目(81971888)
江苏省六大人才高峰项目(TD-SWYY-003)。
关键词
机器学习
脓毒症
诊断
治疗
Machine learning
Sepsis
Diagnosis
Treatment
