Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-Driven Improvements in a Post-Covid World
Language: English
Published by Cambridge University Press, 2022
- Hardcover
- New
Seller: moluna, Greven, Germanymoluna
AbeBooks seller since July 9, 2020
Condition: New
£ 91.24
Quantity: Over 20 available
Add to basketItem description from seller
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This overview of interdisciplinary research partnerships applying AI, IE, and OR in societal and operational problems in a variety of healthcare settings highlights how engineering has contributed to medical knowledge, health system operations, and behavior.
Seller Inventory # 498364117
- Title
- Artificial Intelligence for Healthcare: Interdisciplinary Partnerships for Analytics-Driven Improvements in a Post-Covid World
- Publisher
- Cambridge University Press
- Publication year
- 2022
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1108836739
- ISBN 13
- 9781108836739
- Seller catalogs
- Importe
"Synopsis" may belong to another edition of this title.
About the Author
David Scheinker is a Clinical Associate Professor of Pediatrics in the Stanford School of Medicine and the Executive Director of Systems Design and Collaborative Research at the Stanford Lucile Packard Children's Hospital. He is the Founder and Director of SURF Stanford Medicine (surf.stanford.edu), a group that brings together students and faculty from the university with physicians, nurses, and administrators from the hospitals to improve the quality of care using operations research methodology. His research focuses on applications of operations research in healthcare. Previously, he was a Joint Research Fellow at The MIT Sloan School of Management and Massachusetts General Hospital.
Eva Enns is an Associate Professor in the Division of Health Policy and Management at the University of Minnesota School of Public Health. She received her PhD in Electrical Engineering from Stanford University in 2012 and her dissertation was awarded the Decision Sciences Institute Elwood S. Buffa Doctoral Dissertation Award in 2013. In her research, she applies engineering concepts, including simulation modelling, optimization, cost-effectiveness analysis, and resource allocation, to help inform policies for the prevention and treatment of infectious diseases. Specific application areas include HIV, sexually transmitted infections, antimicrobial resistance, and most recently COVID-19.
"About the title" may belong to another edition of this title.
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