Use of Artificial Intelligence in Healthcare Delivery

S. Reddy
{"title":"Use of Artificial Intelligence in Healthcare Delivery","authors":"S. Reddy","doi":"10.5772/INTECHOPEN.74714","DOIUrl":null,"url":null,"abstract":"In recent years, there has been an amplified focus on the use of artificial intelligence (AI) in various domains to resolve complex issues. Likewise, the adoption of artificial intelligence (AI) in healthcare is growing while radically changing the face of healthcare delivery. AI is being employed in a myriad of settings including hospitals, clinical laboratories, and research facilities. AI approaches employing machines to sense and comprehend data like humans have opened up previously unavailable or unrecognisedopportunities for clinical practitioners and health service organisations. Some examples include utilising AI approaches to analyse unstructured data such as photos, videos, physician notes to enable clinical decision making; use of intelligence interfaces to enhance patient engagement and compliance with treatment; and predictive modelling to manage patient flow and hospital capacity/resource allocation. Yet, there is an incomplete understanding of AI and even confusion as to what it is? Also, it is not completely clear what the implications are in using AI generally and in particular for clinicians? This chapter aims to cover these topics and also introduce the reader to the concept of AI, the theories behind AI programming and the various applications of AI in the medical domain.","PeriodicalId":430102,"journal":{"name":"eHealth - Making Health Care Smarter","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"eHealth - Making Health Care Smarter","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.74714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

Abstract

In recent years, there has been an amplified focus on the use of artificial intelligence (AI) in various domains to resolve complex issues. Likewise, the adoption of artificial intelligence (AI) in healthcare is growing while radically changing the face of healthcare delivery. AI is being employed in a myriad of settings including hospitals, clinical laboratories, and research facilities. AI approaches employing machines to sense and comprehend data like humans have opened up previously unavailable or unrecognisedopportunities for clinical practitioners and health service organisations. Some examples include utilising AI approaches to analyse unstructured data such as photos, videos, physician notes to enable clinical decision making; use of intelligence interfaces to enhance patient engagement and compliance with treatment; and predictive modelling to manage patient flow and hospital capacity/resource allocation. Yet, there is an incomplete understanding of AI and even confusion as to what it is? Also, it is not completely clear what the implications are in using AI generally and in particular for clinicians? This chapter aims to cover these topics and also introduce the reader to the concept of AI, the theories behind AI programming and the various applications of AI in the medical domain.
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
人工智能在医疗服务中的应用
近年来,人们越来越关注在各个领域使用人工智能(AI)来解决复杂问题。同样,人工智能(AI)在医疗保健领域的应用也在不断增长,同时从根本上改变了医疗保健服务的面貌。人工智能正在无数的环境中使用,包括医院、临床实验室和研究机构。人工智能方法利用机器像人类一样感知和理解数据,为临床医生和卫生服务组织开辟了以前无法获得或未被认识的机会。一些例子包括利用人工智能方法分析非结构化数据,如照片、视频、医生笔记,以促进临床决策;使用智能接口来提高患者的参与度和治疗依从性;以及用于管理病人流量和医院容量/资源分配的预测建模。然而,人们对人工智能的理解并不完整,甚至对它是什么感到困惑。此外,目前还不完全清楚人工智能在一般情况下的应用,特别是对临床医生的应用会产生什么影响?本章旨在涵盖这些主题,并向读者介绍人工智能的概念、人工智能编程背后的理论以及人工智能在医疗领域的各种应用。
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
期刊最新文献
Exploring the Interrelationship of Risk Factors for Supporting eHealth Knowledge-Based System Moving towards Sustainable Electronic Health Applications Use of Artificial Intelligence in Healthcare Delivery Using Patient Registries to Identify Triggers of Rare Diseases Phoebe Framework and Experimental Results for Estimating Fetal Age and Weight
×
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