Neuware - IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand.

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Bibliographic Details

Title: IoT-Based Data Analytics for the Healthcare Industry : Techniques and Applications
Publisher: Elsevier Inc Dez 2020
Publication Date: 2020
Language: English
ISBN 10: 0128214724
ISBN 13: 9780128214725
Binding: Taschenbuch
Condition: Neu
Dimensions: 235 millimeters width by 191 millimeters height by 18 millimeters depth
Weight: 590 grams

About this title

Synopsis

IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization.

The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand.

Provides state-of-art methods and current trends in data analytics for the healthcare industry
Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques
Discusses several potential AI techniques developed using IoT for the healthcare industry
Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages

About the Authors

Sanjay Kumar Singh received the M.Tech. degree in computer applications from the IIT (ISM), Dhanbad, India, in 1995, and the Ph.D. degree in computer science and engineering from Uttar Pradesh Technical University, Lucknow, India, in 2004. He is currently a Professor with the Department of Computer Science and Engineering, IIT (BHU) Varanasi, Varanasi, India. He has authored or coauthored more than 150 national and international journal publications, book chapters, and conference papers. His current research interests include biometrics, computer vision, image and video processing, pattern recognition, and artificial intelligence. Dr. Singh is a member of the ACM and Computer Society of India. He is a Guest Editorial Board Member, a reviewer for various journals, and a TPC Member for various conferences.

Ravi Shankar Singh is Associate Professor at Department of Computer Science and Engineering, IIT (BHU), Varanasi, India. He received his B. Tech., M. Tech. and Ph.D., all in Computer Science and Engineering. His research interests include Algorithms and High Performance Computing. He has authored several research publications and one book. He has conducted many workshops/seminars in various areas of Computer Science and Engineering. He has served as reviewer of many reputed international journals.

Anil Kumar Pandey completed his master degree in Mathematics and Postgraduate Diploma in Computer Science Application. He has done Master in Computer Science and Computer Application. He has done Ph.D in Computer Science He is working as Programmer in Banaras Hindu University. He has about 32 years experience of teaching and Research. Dr. Pandey have exposure of community based data analysis. He has assisted more than 20 Ph.D. students in Science, Humanities and Medicine. He has expertise in relational data base management system, AI and machine learning and IOT.

Sandeep S. Udmale received the B.E. degree in computer engineering from the University of Mumbai, Mumbai, India, in 2006, and the M.Tech. degree in computer engineering from Dr. Babasaheb Ambedkar Technological University, Raigad, India, in 2009. He is currently pursuing the Ph.D. degree in computer science and engineering with IIT (BHU) Varanasi, Varanasi, India. He is currently an Assistant Professor with the Department of Computer Engineering and Information Technology, Veermata Jijabai Technological Institute, Mumbai, India. His current research interests include machine learning, data science, and optimization and pattern analysis. Mr. Udmale is a member of the ACM and Computer Society of India.

Ankit Chaudhary is an Assistant Professor at Dept. of Computer Science, The University of Missouri at Saint Louis. He received his B.Tech., M.Eng. and Ph.D., all in Computer Engineering. His research interests include Data Science, Computer Vision and Cyber Security. He has authored seventy research publications and two books. He is an Associate Editor of Computers and Electrical Engineering, an Elsevier Journal. Also he is on the Editorial Board of several International Journals and serves as Program Chair/TPC in many Conferences. He served as federal grant reviewer and also a reviewer for Journals including IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, IEEE Trans. on Visualization & Computer Graphics, IET Computer Vision, IET Image Processing, ACM Trans. on Interactive Intelligent Systems, Signal Image and Video Processing, Robotics and Autonomous Systems.

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