Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review

IF 0.3 Q3 MEDICINE, GENERAL & INTERNAL Galician Medical Journal Pub Date : 2023-11-06 DOI:10.21802/e-gmj2023-a06
Gopal Singh Charan, Ashok Singh Charan, Mandeep Singh Khurana, Gursharn Singh Narang
{"title":"Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review","authors":"Gopal Singh Charan, Ashok Singh Charan, Mandeep Singh Khurana, Gursharn Singh Narang","doi":"10.21802/e-gmj2023-a06","DOIUrl":null,"url":null,"abstract":"Introduction. The intensive care unit (ICU) plays a pivotal role in providing specialized care to patients with severe illnesses or injuries. As a critical aspect of healthcare, ICU admissions demand immediate attention and skilled care from healthcare professionals. However, the intricacies involved in this process necessitate analytical solutions to ensure effective management and optimal patient outcomes.
 Aim. The aim of this review was to highlight the enhancement of the ICUs through the application of analytics, artificial intelligence, and machine learning.
 Methods. The review approach was carried out through databases such as MEDLINE, Embase, Web of Science, Scopus, Taylor & Francis, Sage, ProQuest, Science Direct, CINAHL, and Google Scholar. These databases were chosen due to their potential to offer pertinent and comprehensive coverage of the topic while reducing the likelihood of overlooking certain publications. The studies for this review involved the period from 2016 to 2023.
 Results. Artificial intelligence and machine learning have been instrumental in benchmarking and identifying effective practices to enhance ICU care. These advanced technologies have demonstrated significant improvements in various aspects.
 Conclusions. Artificial intelligence, machine learning, and data analysis techniques significantly improved critical care, patient outcomes, and healthcare delivery.","PeriodicalId":12537,"journal":{"name":"Galician Medical Journal","volume":"22 9","pages":"0"},"PeriodicalIF":0.3000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Galician Medical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21802/e-gmj2023-a06","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction. The intensive care unit (ICU) plays a pivotal role in providing specialized care to patients with severe illnesses or injuries. As a critical aspect of healthcare, ICU admissions demand immediate attention and skilled care from healthcare professionals. However, the intricacies involved in this process necessitate analytical solutions to ensure effective management and optimal patient outcomes. Aim. The aim of this review was to highlight the enhancement of the ICUs through the application of analytics, artificial intelligence, and machine learning. Methods. The review approach was carried out through databases such as MEDLINE, Embase, Web of Science, Scopus, Taylor & Francis, Sage, ProQuest, Science Direct, CINAHL, and Google Scholar. These databases were chosen due to their potential to offer pertinent and comprehensive coverage of the topic while reducing the likelihood of overlooking certain publications. The studies for this review involved the period from 2016 to 2023. Results. Artificial intelligence and machine learning have been instrumental in benchmarking and identifying effective practices to enhance ICU care. These advanced technologies have demonstrated significant improvements in various aspects. Conclusions. Artificial intelligence, machine learning, and data analysis techniques significantly improved critical care, patient outcomes, and healthcare delivery.
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
分析应用人工智能和机器学习对加强重症监护病房的影响:叙述性回顾
介绍。重症监护室(ICU)在为患有严重疾病或受伤的患者提供专门护理方面起着关键作用。作为医疗保健的一个关键方面,ICU入院需要医疗保健专业人员的立即关注和熟练护理。然而,这一过程中涉及的复杂性需要分析解决方案,以确保有效的管理和最佳的患者结果。 的目标。这篇综述的目的是强调通过分析学、人工智能和机器学习的应用来增强icu。 方法。综述方法通过MEDLINE、Embase、Web of Science、Scopus、Taylor &Francis, Sage, ProQuest, Science Direct, CINAHL和Google Scholar。之所以选择这些数据库,是因为它们有可能提供有关该主题的全面报道,同时减少忽视某些出版物的可能性。本综述的研究涉及2016年至2023年期间。结果。人工智能和机器学习在制定基准和确定有效实践以加强ICU护理方面发挥了重要作用。这些先进技术在各个方面都有了显著的改进。 结论。人工智能、机器学习和数据分析技术显著改善了重症监护、患者预后和医疗保健服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
6 weeks
期刊最新文献
Multiple Myeloma Patient with Secondary Liver and Tongue Involvement, Complicated by COVID-19-Induced ARDS: An Autopsy Case Report and Literature Review Medical Students’ Knowledge, Attitude, Practice, and Perceived Barriers Towards Medical Research: A Cross-Sectional Study Three Decades of Progress and Commitment: Brief Historical Landmarks of ‘Galician Medical Journal’ Journey Treatment of Teeth with Root Resorptions: A Case Report and Systematic Review Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review
×
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