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Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-Driven Improvements in a Post-Covid World
Sze-Chuan Suen
(Illustrated by)
·
David Scheinker
(Illustrated by)
·
Eva Enns
(Illustrated by)
·
Cambridge University Press
· Hardcover
Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-Driven Improvements in a Post-Covid World - Suen, Sze-Chuan ; Scheinker, David ; Enns, Eva
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Origin: U.S.A.
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Synopsis "Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-Driven Improvements in a Post-Covid World"
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.
