Predictive Modelling in Biomedical Data Mining and Analysis
Language: English
Published by Academic Press, 2022
- Softcover
- New

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- Title
- Predictive Modelling in Biomedical Data Mining and Analysis
- Publisher
- Academic Press
- Publication year
- 2022
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 032399864X
- ISBN 13
- 9780323998642
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference.
Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information.
- Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification
- Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks
- Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
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About the Author
Dr. Lalit Mohan Goyal has completed Ph.D. from Jamia Millia Islamia, New Delhi, in Computer Engineering; M.Tech (Honors) in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi; and B.Tech (Honors) in Computer Engineering from Kurukshetra University, Kurukshetra. He has 17 years of teaching experience in the area of Theory of Computation, Parallel and Random algorithms, Distributed Data Mining & Cloud Computing. He has completed a project sponsored by the Indian Council of Medical Research, Delhi. He has published and communicated more than 40 research papers and attended many workshops, FDPs and Seminars. He has filed nine patents in the area of Artificial Intelligence and Deep Learning. He is the reviewer of many reputed journals, conferences book series. Presently, He is working in Department of Computer Engineering, J.C. Bose University of Science & Technology, YMCA, Faridabad.
Dr. Valentina Emilia Balas is Full Professor in the Department of Automatics and Applied Software, Faculty of Engineering, Aurel Vlaicu University of Arad, Romania. She holds a PhD in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Her research interests include intelligent systems, fuzzy systems, soft computing, smart sensors, information fusion, modeling, and simulation.
Dr. Balas serves as Director of the Intelligent Systems Research Center and Director of International Relations, Programs and Projects at Aurel Vlaicu University of Arad. She is Editor-in-Chief of the International Journal of Advanced Intelligence Paradigms and International Journal of Computational Systems Engineering, and serves on the editorial boards of several scientific journals. She has led and contributed to numerous national and international research initiatives, including the European Union-funded BioCell-NanoART project on bio-inspired cellular nano-architectures. She is active in several professional societies and technical committees, including IEEE, the European Society for Fuzzy Logic and Technology, and the Society for Industrial and Applied Mathematics.
Dr. Basant Agarwal works as an Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India, which is an Institute of National Importance. He holds a Ph.D. and M.Tech. from the Department of Computer Science and Engineering, Malaviya National Institute of Technology Jaipur, India. He has more than 9 years of experience in research and teaching. He has worked as a Postdoc Research Fellow at the Norwegian University of Science and Technology (NTNU), Norway, under the prestigious ERCIM (European Research Consortium for Informatics and Mathematics) fellowship in 2016. He has also worked as a Research Scientist at Temasek Laboratories, National University of Singapore (NUS), Singapore. His research interest include Artificial Intelligence, Cyber physical systems, Text mining, Natural Language Processing, Machine learning, Deep learning, Intelligent Systems, Expert Systems and related areas.
Dr. Mamta Mittal works as Head and Associate Professor (Data Analytics and Data Science) in Delhi Skill & Entrepreneurship University (under Government of NCT Delhi), New Delhi. She received a PhD in Computer Science and Engineering from Thapar University, Patiala; MTech (Honors) in Computer Science & Engineering from YMCA, Faridabad; and B. Tech in Computer Science & Engineering from Kurukshetra University, Kurukshetra, in 2001. She has been teaching for the last 18 years with emphasis on Data Mining, Machine Learning, DBMS and Data Structure. Dr. Mittal is a lifetime member of CSI and published more than 80 research papers. She holds five patents, two of which have been granted copyrights, and three more published in the area of Artificial Intelligence, IoT and Deep Learning. Dr. Mittal has edited/authored many books with reputed publishers, and is working on DST approved Project “Development of IoT based hybrid navigation module for mid-sized autonomous vehicles. Currently, she is guiding PhD scholars in Machine Learning, Computer Vision and Deep Learning areas. Dr. Mittal is Editorial Board member with Inder-Science, Bentham Science, Springer and Elsevier, handled Special issues, has chaired many Conferences.
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