Practical Data Analytics for Innovation in Medicine (2nd Edition) is a comprehensive guide to applying AI, machine learning, and predictive analytics in modern healthcare. This PDF eBook explains how data-driven models improve patient care, reduce costs, and support smarter medical decisions.
Covering real-world case studies, step-by-step tutorials, and healthcare applications, the book explores how predictive and prescriptive analytics are used in:
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Personalized medicine
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Medical research
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Clinical decision support
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Healthcare administration
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Pandemic response (including COVID-19)
Written by industry experts Gary D. Miner, Linda A. Miner, Scott Burk, Mitchell Goldstein, Robert Nisbet, Nephi Walton, and Thomas Hill, this 2023 edition provides both historical context and future insights into data analytics in medicine.
📘 eBook Details
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Format: PDF
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Pages: 578
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Language: English
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Publisher: Academic Press
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Edition: 2nd (2023)
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ISBN-13: 9780323952743
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File Size: 23.02 MB
Perfect for healthcare professionals, data scientists, researchers, policymakers, and students seeking practical knowledge on AI-powered medical innovation.