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

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

9781108836739
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Description
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.
Product Details
99307
9781108836739
9781108836739

Data sheet

Publication date
2022
Issue number
1
Cover
hard cover
Pages count
350
Dimensions (mm)
157.00 x 235.00
Weight (g)
437
  • Introduction Sze-chuan Suen, Eva Enns and David Scheinker; 1. Artificial Intelligence and Public Health:: Opportunities Abound Sheldon H. Jacobson and Janet A. Jokela; Part I. Personalized Medicine:: 2. How AI Can Help Depression Care - Designing Patient-Specific Adaptive Monitoring Algorithms Shan Liu and Shuai Huang; 3. Personalizing Medicine -Estimating Heterogeneous Treatment Effects Tony Duan and Sanjay Basu; 4. Proceed with Care - Integrating Predictive Analytics with Patient Decision-Making Hamsa Bastani and Pengyi Shi; Part II. Optimizing Health Care Systems:: 5. Using Algorithmic Solutions to Address Gatekeeper Training Issues on College Campuses Anthony Fulginiti, Aida Rahmattalabi, Jarrod Call, Phebe Vayanos, and Eric Rice; 6. Optimizing Defibrillator Deployment Timothy C.Y. Chan and Christopher L.F. Sun; 7. Optimization of Biomarker-Based Prostate Cancer Screening Policies Christine Barnett and Brian Denton; 8. Analytics-Driven Hospital Resource Management - Principles and Practical Lessons from Projects at Three Hospitals Margaret L. Brandeau and David Scheinker; 9. Practical advice for clinician-engineer partnerships for the use of AI, optimization, and analytics for healthcare delivery David Scheinker, Robert A. Harrington, and Fatima Rodriguez.
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