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Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-driven Improvements in a Post-COVID World

LeeAndro

Trusted Editor
Trusted Editor
Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-driven Improvements in a Post-COVID World
English | 350 pages | Cambridge University Press; New edition (May 5, 2022) | 1108836739 | PDF | 9.07 Mb

Healthcare has recently seen numerous exciting applications of artificial intelligence, industrial eeering, 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, rag from optimizing the location of AEDs for cardiac arrests to data mining for facilitating patient flow through a hospital. These applications highlight how eeering has contributed to medical knowledge, health system operations, and behavioral health. Chapter authors include medical doctors, policy-makers, social scientists, and eeers. Each chapter bs with a summary of the health care problem and eeering method. In these examples, researchers in public health, medicine, and social science as well as eeers will find a path to start interdisciplinary collaborations in health applications of AI/IE/OR.



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