Artificial intelligence for healthcare : interdisciplinary partnerships for analytics-driven improvements in a Post-COVID world / edited by Sze-chuan Suen, University of Southern California, David Scheinker, Stanford University, Eva Enns, University of Minnesota.
Material type: TextLanguage: English Cambridge : Cambridge University Press, 2022Description: 1 online resource (x, 192 pages) : digital, PDF file(s)Content type:- text
- online resource
- 9781108872188 (ebook)
- 362.1029
- R858 .A768 2022
Item type | Current library | Call number | URL | Status | Barcode | |
---|---|---|---|---|---|---|
E-Book | Ranganathan Library | 362.1029 (Browse shelf(Opens below)) | Link to resource | Available | E01838 |
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.
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