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Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-driven Improvements in a Post-COVID World.
・ISBN 978-1-108-83673-9 hard GB£ 73.00
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| 著者・編者 | Suen, Sze-chuan / Scheinker, David / Enns, Eva (eds.), |
|---|---|
| 出版社 | (Cambridge University Press, UK) |
| 出版年月 | 2022 |
| ページ数 | 204 pp. |
| 言語 | ENG |
| ニュース番号 | <A00-85> |
解説
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.