Medicinsk & sundhedsfaglig informatik
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Practical Data Analytics for Innovation in Medicine
Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies
Udgivet af Elsevier Science & Technology
ISBN
9780323952743
Om denne bog
Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important…
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Bogdetaljer
Forfatter
Gary D. (CEO Miner, Linda A. (Professor Emeritus, Director of Academic Programs Miner, Thomas (StatSoft Hill, Robert (Researcher-Medical Informatics Nisbet, Scott (Chief Data Officer Burk, Robert Nisbet, Gary D. Miner, Scott Burk, Mitchell (Professor of Pediatrics Goldstein, Nephi (Associate Medical Director Walton, Thomas Hill, Linda A. Miner, Mitchell Goldstein, Nephi Walton
Forlag
Elsevier Science & Technology
Kategori
Medicinsk & sundhedsfaglig informatik
ISBN-13
9780323952743
EAN
9780323952743
Format
Indbundet
Sprog
Engelsk
sider
576
Undertitel
- Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies
Produktbeskrivelse
Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics.
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