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

IF 0.3 Q3 MEDICINE, GENERAL & INTERNAL
Gopal Singh Charan, Ashok Singh Charan, Mandeep Singh Khurana, Gursharn Singh Narang
{"title":"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","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":"{\"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}","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

摘要

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。
Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review
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.
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
审稿时长
6 weeks
×
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