机器学习:生物医学研究人员概述

A. Farhat, N. Shah, Z. Wang, L. Råman
{"title":"机器学习:生物医学研究人员概述","authors":"A. Farhat, N. Shah, Z. Wang, L. Råman","doi":"10.15761/JTS.1000343","DOIUrl":null,"url":null,"abstract":"Machine learning is a sub-field of artificial intelligence. It is a field that involves computer algorithms that are given the capability to learn from data. This results in model generation of complex rules from the data itself, rather than from relying on strict rubrics inputted manually. Relationships between inputted data [variables such as demographics, physiological data, laboratory values, etc.] and outcomes [mortality, presence of infection, acute kidney injury, etc.] can be uncovered even when not immediately obvious to a trained expert. In recent years, there has been a surge of literature using machine learning in healthcare research; some articles are highlighted in Table 1 [3-7].","PeriodicalId":74000,"journal":{"name":"Journal of translational science","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Machine learning: Brief overview for biomedical researchers\",\"authors\":\"A. Farhat, N. Shah, Z. Wang, L. Råman\",\"doi\":\"10.15761/JTS.1000343\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning is a sub-field of artificial intelligence. It is a field that involves computer algorithms that are given the capability to learn from data. This results in model generation of complex rules from the data itself, rather than from relying on strict rubrics inputted manually. Relationships between inputted data [variables such as demographics, physiological data, laboratory values, etc.] and outcomes [mortality, presence of infection, acute kidney injury, etc.] can be uncovered even when not immediately obvious to a trained expert. In recent years, there has been a surge of literature using machine learning in healthcare research; some articles are highlighted in Table 1 [3-7].\",\"PeriodicalId\":74000,\"journal\":{\"name\":\"Journal of translational science\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of translational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15761/JTS.1000343\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of translational science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15761/JTS.1000343","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

机器学习是人工智能的一个子领域。这是一个涉及计算机算法的领域,计算机算法具有从数据中学习的能力。这导致从数据本身生成复杂规则的模型,而不是依赖于手动输入的严格规则。输入数据(如人口统计、生理数据、实验室值等变量)和结果(死亡率、感染、急性肾损伤等)之间的关系,即使对训练有素的专家来说不是很明显,也可以发现。近年来,在医疗保健研究中使用机器学习的文献激增;部分文章在表1中突出显示[3-7]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Machine learning: Brief overview for biomedical researchers
Machine learning is a sub-field of artificial intelligence. It is a field that involves computer algorithms that are given the capability to learn from data. This results in model generation of complex rules from the data itself, rather than from relying on strict rubrics inputted manually. Relationships between inputted data [variables such as demographics, physiological data, laboratory values, etc.] and outcomes [mortality, presence of infection, acute kidney injury, etc.] can be uncovered even when not immediately obvious to a trained expert. In recent years, there has been a surge of literature using machine learning in healthcare research; some articles are highlighted in Table 1 [3-7].
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
自引率
0.00%
发文量
0
期刊最新文献
Bell’s palsy and lip HSV-1 infection: importance of subcutaneous access Clinical research reactivation during the COVID-19 pandemic: An academic center process and lessons for the future. Bell's palsy and lip HSV-1 infection: importance of subcutaneous access. Attitudes towards clinical trial participation among people living with chronic hepatitis B How smell regulates metabolism: The role of ectopically expressed olfactory receptors in lipid and glucose homeostasis
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1