Overview
- Focuses on various advanced technologies of machine learning
- Presents insight about techniques which predictive, proactive, and preventative
- Serves as a future guide for researchers and practitioners in academia and industry
Part of the book series: Studies in Computational Intelligence (SCI, volume 936)
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Table of contents (19 chapters)
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Front Matter
Keywords
About this book
Editors and Affiliations
About the editors
Dr. Hrudaya Kumar Tripathy is an Associate Professor of the School of Computer Engineering, KIIT University, Bhubaneswar, India. He has completed a Doctorate in Computer Science from Berhampur University, a Master in Computer Science Engineering from the Indian Institute of Technology, Guwahati, and received Post-Doctoral Fellowship from the Ministry of Higher Education Malaysia. He has 20 years of teaching experience with post doctorate research experience. He had been Visiting Faculty for a couple of years in Asia Pacific University, Kuala Lumpur, Malaysia, and the University of Utara Malaysia, Sintok, Malaysia. Dr.Tripathy awarded a Young IT professional award in 2013 on a regional level from the Computer Society of India (CSI). He has more than 100 research publications in different national/international journals and conferences to his credit.
Dr. Sushruta Mishra is an Indian by birth. He completed his B.Tech. from ITER, Bhubaneswar, in 2009. He pursued his M.Tech. degree from IIIT, Bhubaneswar, in 2012. He completed his Ph.D. from KIIT University, Bhubaneswar, in 2017. Currently, he is working as Assistant Professor in KIIT University, Bhubaneswar, in the School of Computer Engineering. He has a good 7 years of academic teaching experience. Her prime research area of interest includes machine learning, sentiment analysis, cognitive computing and robotics. Dr. Mishra has published more than 60 research and development articles in various reputed journals, conferences and book chapters.
Dr. Pradeep Kumar Mallick is currently working as Senior Associate Professor in the School of Computer Engineering , KIIT Deemed to be University, India .He has also served as Professor and Head Department of Computer Science and Engineering,Vignana Bharathi Institute of Technology, Hyderabad. He has completed his Post Doctoral Fellowship from Kongju National University South Korea,PhD from Siksha Ó’ Anusandhan University, India and Master degree from Bijupatnaik Unversity ,Odisha . Besides academics, he is also involved in various administrative activities, Member of Board of Studies , Member of Doctoral Research Evaluation Committee, Admission Committee etc.Now he is the editorial member of Korean Convergence Society for SMB.He has published 12 edited books,1 text Book and more than 100 research papers in National and international journals and conference proceedings to his credit.
Dr. Amiya Ranjan Panda has seven years of research experience in DRDO Chandipur and more than three years of teaching experience. He received B.Tech. degree in Information Technology from Biju Patnaik University of Technology, Odisha, India, in 2009, M.Tech. degree in Computer Science and Engineering from the KIIT University, India in 2012. and Ph.D. degree from Siksha ‘O’ Anusandhan University, Odisha, in the year 2017 . Currently, he is working as Assistant Professor in KIIT Deemed to be University, Bhubaneswar. His research interest is machine learning, IoT, data acquisition system and software-defined radio. He has published more than 25 articles in international journals. Currently he is working with a real-time project of DRDO.
Bibliographic Information
Book Title: Technical Advancements of Machine Learning in Healthcare
Editors: Hrudaya Kumar Tripathy, Sushruta Mishra, Pradeep Kumar Mallick, Amiya Ranjan Panda
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-981-33-4698-7
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
Hardcover ISBN: 978-981-33-4697-0Published: 28 February 2021
Softcover ISBN: 978-981-33-4700-7Published: 01 March 2022
eBook ISBN: 978-981-33-4698-7Published: 27 February 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIII, 388
Number of Illustrations: 58 b/w illustrations, 138 illustrations in colour
Topics: Computational Intelligence, Machine Learning, Artificial Intelligence, Health Informatics