Big Data Analytics in Healthcare (eBook)

Artikelnummer: 978-3-030-31672-3
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations.

The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.


This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations.

The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.


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VerlagSpringer International Publishing
EinbandPDF
Erscheinungsjahr2019
Seitenangabe187 S.
AusgabekennzeichenEnglisch
AbbildungenXI, 187 p. 55 illus., 37 illus. in color.
Masse4'827 KB
PlattformPDF
ReiheStudies in Big Data; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorKulkarni, Anand J. (Hrsg.) / Siarry, Patrick (Hrsg.) / Singh, Pramod Kumar (Hrsg.) / Abraham, Ajith (Hrsg.) / Zhang, Mengjie (Hrsg.) / Zomaya, Albert (Hrsg.) / Baki, Fazle (Hrsg.)

Alle Bände der Reihe "Studies in Big Data; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

Über den Autor Anand J. (Hrsg.) Kulkarni

Anand J Kulkarni holds a PhD in Artificial Intelligence (AI) based Distributed Optimization from Nanyang Technological University, Singapore, MS in AI from University of Regina, Canada. He worked as Postdoctoral Research Fellow at Odette School of Business, University of Windsor, Canada. Since 2021, he is working as Research Professor and Associate Director of the Institute of Artificial Intelligence at the MITWPU, Pune, India. His research interests include AI based Nature Inspired optimization algorithms, and self-organizing systems. Anand pioneered optimization methodologies such as cohort intelligence, ideology algorithm, expectation algorithm, socio evolution & learning optimization algorithm leader-advocate-believer based algorithm and snail homing & mating search algorithm. Dr. Anand has published over 120 research papers in peer-reviewed reputed journals, chapters and conferences along with 7 authored and 15 edited books. He has guided 6 doctoral, 10 master's and over 60 UG students. Dr. Anand is the lead series editor for several reputed publishers. He is the recipient of the best paper award in IEEE ICNSC, Chicago, USA and 'Swatantryveer Savarakar Award' 2023 by 'Pune Marathi Granthalay', Pune for his Marathi book entitled 'Artificial Intelligencechya Watewar'. Apoorva S Shastri holds a PhD in Optimization Algorithms and Applications from Symbiosis International (Deemed University), Master of Technology (M.Tech) in VLSI Design and Bachelor of Engineering in Electronics & Product Design Technology from R.T.M.N.U, Nagpur. She has also done a Diploma from the Govt. Polytechnic, Nagpur. She worked as a guest faculty at Centre for Development of Advanced Computing (C-DAC), Pune. Currently, she is a Research Assistant Professor at Institute of Artificial Intelligence at the MITWPU, Pune, India. Her research interests include optimization algorithms, VLSI design, multi-objective optimization, continuous, discrete, and combinatorial optimization, complex systems, manufacturing, and self-organizing systems. Dr. Apoorva developed socio-inspired optimization methodologies such as multi-cohort intelligence algorithm, expectation algorithm and LAB algorithm, and snail homing and mating search algorithm. Dr. Apoorva has published several research papers in peer reviewed journals, chapters, and conferences along with 1 authored and 5 edited books. Hossein Bonakdari is an Associate Professor of Civil Engineering at the University of Ottawa, specializing in AI-driven hydrology, hydraulics, wildfire/flood modeling, and climate resilience. He has published over 310 papers and authored four books. Dr. Bonakdari develops advanced algorithms to extract insights from big datasets. His innovative work addresses pressing environmental challenges, including floods, droughts, and wildfires, while making significant contributions to both national and international research communities.

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