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Practical Data Analytics for Innovation in Medicine

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Author :
Release : 2023
Genre : Artificial intelligence
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Practical Data Analytics for Innovation in Medicine by : Gary Miner

Download or read book Practical Data Analytics for Innovation in Medicine written by Gary Miner. This book was released on 2023. Available in PDF, EPUB and Kindle. Book excerpt:

Practical Data Analytics for Innovation in Medicine

Download Practical Data Analytics for Innovation in Medicine PDF Online Free

Author :
Release : 2023-02-08
Genre : Computers
Kind : eBook
Book Rating : 755/5 ( reviews)

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Book Synopsis Practical Data Analytics for Innovation in Medicine by : Gary D. Miner

Download or read book Practical Data Analytics for Innovation in Medicine written by Gary D. Miner. This book was released on 2023-02-08. Available in PDF, EPUB and Kindle. Book excerpt: 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

Data Analytics in Medicine

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Author :
Release : 2019-11-18
Genre :
Kind : eBook
Book Rating : 043/5 ( reviews)

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Book Synopsis Data Analytics in Medicine by : Information Resources Management Association

Download or read book Data Analytics in Medicine written by Information Resources Management Association. This book was released on 2019-11-18. Available in PDF, EPUB and Kindle. Book excerpt: ""This book examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations"--

Data Science for Healthcare

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Author :
Release : 2019-02-23
Genre : Computers
Kind : eBook
Book Rating : 494/5 ( reviews)

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Book Synopsis Data Science for Healthcare by : Sergio Consoli

Download or read book Data Science for Healthcare written by Sergio Consoli. This book was released on 2019-02-23. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications

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Release : 2019-12-06
Genre : Medical
Kind : eBook
Book Rating : 057/5 ( reviews)

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Book Synopsis Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources. This book was released on 2019-12-06. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.

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