Description
English | 2023 | PDF | 75 MB | 543 Pages
Gary Miner, 9780323952743, 978-0323952743, 978-0-323-95274-3, 0323952747, 0323952755, 9780323952750, 978-0323952750, B0BVBLS274
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.
Brings
a historical perspective in medical care to discuss both the current
status of health care delivery worldwide and the importance of using
modern predictive analytics to help solve the health care crisis Provides
online tutorials on several predictive analytics systems to help
readers apply their knowledge on today’s medical issues and basic
research Teaches how to develop
effective predictive analytic research and to create
decisioning/prescriptive analytic systems to make medical decisions
quicker and more accurate
