東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Artificial intelligence for healthca...

Suen, Sze-chuan.

FindBook

Google Book

Amazon

博客來

Artificial intelligence for healthcare = interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence for healthcare/ edited by Sze-chuan Suen, University of Southern California, David Scheinker, Stanford University, Eva Enns, University of Minnesota.
其他題名:	interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world /
其他作者:	Suen, Sze-chuan.
出版者:	Cambridge :Cambridge University Press, : 2022.,
面頁冊數:	x, 192 p. :ill., digital ;23 cm.
附註:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
標題:	Medical informatics. -
電子資源:	https://doi.org/10.1017/9781108872188
ISBN:	9781108872188

Artificial intelligence for healthcare = interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world /
Artificial intelligence for healthcareinterdisciplinary partnerships for analytics-driven improvements in a Post-COVID world /[electronic resource] :edited by Sze-chuan Suen, University of Southern California, David Scheinker, Stanford University, Eva Enns, University of Minnesota. - Cambridge :Cambridge University Press,2022. - x, 192 p. :ill., digital ;23 cm.

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

Healthcare has recently seen numerous exciting applications of artificial intelligence, industrial engineering, and operations research. This book, designed to be accessible to a diverse audience, provides an overview of interdisciplinary research partnerships that leverage AI, IE, and OR to tackle societal and operational problems in healthcare. The topics are drawn from a wide variety of disciplines, ranging from optimizing the location of AEDs for cardiac arrests to data mining for facilitating patient flow through a hospital. These applications highlight how engineering has contributed to medical knowledge, health system operations, and behavioral health. Chapter authors include medical doctors, policy-makers, social scientists, and engineers. Each chapter begins with a summary of the health care problem and engineering method. In these examples, researchers in public health, medicine, and social science as well as engineers will find a path to start interdisciplinary collaborations in health applications of AI/IE/OR.

ISBN: 9781108872188Subjects--Topical Terms:

661258
Medical informatics.

LC Class. No.: R858 / .A768 2022

Dewey Class. No.: 362.10285

National Library of Medicine Call No.: W 26.5

Artificial intelligence for healthcare = interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world /
LDR:02052nmm a2200253 a 4500 001 2324589
003 UkCbUP
005 20220502145410.0
006 m d
007 cr nn 008maaau
008 231215s2022 enk o 1 0 eng d
020 $a 9781108872188 $q (electronic bk.)
020 $a 9781108836739 $q (hardback)
035 $a CR9781108872188
040 $a UkCbUP $b eng $c UkCbUP $d GP
050 0 0 $a R858 $b .A768 2022
060 4 $a W 26.5
082 0 0 $a 362.10285 $2 23
090 $a R858 $b .A791 2022
245 0 0 $a Artificial intelligence for healthcare $h [electronic resource] : $b interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world / $c edited by Sze-chuan Suen, University of Southern California, David Scheinker, Stanford University, Eva Enns, University of Minnesota.
260 $a Cambridge : $b Cambridge University Press, $c 2022.
300 $a x, 192 p. : $b ill., digital ; $c 23 cm.
500 $a Title from publisher's bibliographic system (viewed on 07 Apr 2022).
520 $a Healthcare has recently seen numerous exciting applications of artificial intelligence, industrial engineering, and operations research. This book, designed to be accessible to a diverse audience, provides an overview of interdisciplinary research partnerships that leverage AI, IE, and OR to tackle societal and operational problems in healthcare. The topics are drawn from a wide variety of disciplines, ranging from optimizing the location of AEDs for cardiac arrests to data mining for facilitating patient flow through a hospital. These applications highlight how engineering has contributed to medical knowledge, health system operations, and behavioral health. Chapter authors include medical doctors, policy-makers, social scientists, and engineers. Each chapter begins with a summary of the health care problem and engineering method. In these examples, researchers in public health, medicine, and social science as well as engineers will find a path to start interdisciplinary collaborations in health applications of AI/IE/OR.
650 0 $a Medical informatics. $3 661258
650 0 $a Medical care $x Data processing. $3 661308
650 0 $a Artificial intelligence $x Medical applications. $3 900591
700 1 $a Suen, Sze-chuan. $3 3645946
700 1 $a Scheinker, David. $3 3645947
700 1 $a Enns, Eva. $3 3645948
856 4 0 $u https://doi.org/10.1017/9781108872188