关于机器学习在电子健康记录中的当代应用的评论

Q2 Medicine
Jordan Bryan, Didong Li
{"title":"关于机器学习在电子健康记录中的当代应用的评论","authors":"Jordan Bryan, Didong Li","doi":"10.18043/001c.120570","DOIUrl":null,"url":null,"abstract":"Various decisions concerning the management, display, and diagnostic use of electronic health records (EHR) data can be automated using machine learning (ML). We describe how ML is currently applied to EHR data and how it may be applied in the near future. Both benefits and shortcomings of ML are considered.","PeriodicalId":39574,"journal":{"name":"North Carolina Medical Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comments on Contemporary Uses of Machine Learning for Electronic Health Records\",\"authors\":\"Jordan Bryan, Didong Li\",\"doi\":\"10.18043/001c.120570\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various decisions concerning the management, display, and diagnostic use of electronic health records (EHR) data can be automated using machine learning (ML). We describe how ML is currently applied to EHR data and how it may be applied in the near future. Both benefits and shortcomings of ML are considered.\",\"PeriodicalId\":39574,\"journal\":{\"name\":\"North Carolina Medical Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"North Carolina Medical Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18043/001c.120570\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"North Carolina Medical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18043/001c.120570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 1

摘要

有关电子健康记录(EHR)数据的管理、显示和诊断使用的各种决策都可以通过机器学习(ML)实现自动化。我们介绍了目前如何将 ML 应用于电子病历数据,以及在不久的将来可能如何应用。我们考虑了 ML 的优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comments on Contemporary Uses of Machine Learning for Electronic Health Records
Various decisions concerning the management, display, and diagnostic use of electronic health records (EHR) data can be automated using machine learning (ML). We describe how ML is currently applied to EHR data and how it may be applied in the near future. Both benefits and shortcomings of ML are considered.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
North Carolina Medical Journal
North Carolina Medical Journal Medicine-Medicine (all)
CiteScore
1.40
自引率
0.00%
发文量
121
期刊介绍: NCMJ, the North Carolina Medical Journal, is meant to be read by everyone with an interest in improving the health of North Carolinians. We seek to make the Journal a sounding board for new ideas, new approaches, and new policies that will deliver high quality health care, support healthy choices, and maintain a healthy environment in our state.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信