Predictive Data Modelling for Biomedical Data and Imaging

by Poonam Tanwar (Editor), Tapas Kumar (Editor), K. Kalaiselvi (Editor), Haider Raza (Editor), Seema Rawat (Editor)

Overview

In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding.

Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. By exploring diverse case studies and methodologies, this book contributes to the advancement of healthcare practices, ultimately improving patient outcomes and well-being.

Product Details

ISBN-13:	9781040124253
Publisher:	River Publishers
Publication date:	09/13/2024
Series:	River Publishers Series in Biotechnology and Medical Research
Sold by:	Barnes & Noble
Format:	eBook
Pages:	392
File size:	32 MB
Note:	This product may take a few minutes to download.

About the Author

Dr. Poonam Tanwar has 21 years of teaching experience working as professor in Manav Rachna International Institute of Research & Studies, Faridabad. She has published more than 100 research papers in various international journals and conferences, 40 are indexed in Scopus. She has one copyright and filled six patents. She has edited books and was guest editor for special issues of for International Journal of Recent Patents in Engineering (UAE) and one more is in process. She has been awarded a woman researcher award by VDGOODS Academy Chennai, International Inspirational Woman Award 2020. She has organized various science and technology awareness programs for rural development. She received a Certificate of RECOGNITION (Silver Category) for outstanding contribution to the Campus Connect Program for all academic years since 2011 to 2017 by INFOSYS, Chandigarh. She is convenor and coordinator of many technical events like IEEE international conference COM-IT-CON 2019, 2022, International symposium on Computational Intelligence, International Hackhthon (Hack the Mountain), etc. Beside this she is Technical program committee member for various International Conferences Like ICIC 2018, ICFNN, Rome(Italy ), European Conference on Natural Language Processing and Information Retrieval, Berlin(Europe), etc.

Dr. K. Kalaiselvi

received her doctoral degree from Anna University, Chennai, India in 2013 under the Faculty of Science and Humanities. Currently she is working as an Assistant Professor in the Department of Data Analytics, Saveetha College of Liberal Arts and Sciences, SIMATS, Chennai, India. She completed a mini project entitled "Mobile Tracking System for Preventing the Propagation of Feminine Victim" funded by VISTAS Project, developed e-content for the Database Management Systems course, SAP. She has published more than 60 articles in the Scopus indexed journals, Web of Science and UGC Journal and presented more than 20 research papers at international conferences. She filed and published a patent based on Internet of Things applications and has published around five monographs which includes Springer, Emerald publisher. She has acted as reviewer and editorial board member for reputed journals. She received a "Senior Woman Educator & Scholar Award" in the 11th Teachers Day Awards 2020, a "Young Woman Educator & Scholar Award" in the 6th National Women’s Day Awards 2019, and a"Best Researcher Award" from DK International Research Foundation, 2018.

Dr. Tapas Kumar

holds a Ph.D. degree in Engineering (2013), gained at Dept. Of Computer Sc. & Engineering, Birla Institute of Technology, Mesra, Ranchi, (Jharkhand). He received his master’s degree in Computer Science from Guru Jambeshwar University of Science and Technology, India, and a B.E. from Amravati University, Amravati. He has supervised 10 M.Tech theses and guided more than 200 students of B.E/B.Tech in their research-based and application-based projects. Prof. Tapas Kumar has published almost 45 research articles in refereed international journals and15 research papers presented and published in various international and national conferences and scholarly meetings. He has also successfully guided six Ph.D. scholars.

Dr. Haider Raza

received a Ph.D. in Computer Science from University of Ulster, Northern Ireland, UK, a master’s degree in Computer Engineering from Manav Rachna International University, India, and a bachelor’s degree in Computer Science and Engineering from Integral University, India. He completed his primary and secondary education in 1991–2003 from Colvin Taluqdars’ College in Lucknow, which is one of the oldest private schools in India. He was born in the city of Lucknow and spent nearly 24 years there. He has previously worked at Swansea University, Wales, UK, University of Ulster, Northern Ireland, UK, Dilla University, Ethiopia, and Manav Rachna International University, India. He is a Fellow of the Higher Education Academy (FHEA) and a Senior Member of the Institute of Electrical and Electronics Engineers (SMIEEE). His research interests focus on the artificial intelligence machine learning for decision making, non-stationary learning, brain-computer interface, EEG/MEG signal processing, computer vision, and computational intelligence methods for healthcare, businesses, and environment.

Dr. Seema Rawat

is an Associate Professor, Amity School of Engineering and Technology, Amity University Tashkent, Uzbekistan with around 15 years of teaching experience. Her research areas are cloud computing, data mining, artificial intelligence, and big data. She has a lot of research experience and has published more than 100 research papers in international journals and conferences (Scopus indexed) and book chapters, and holds 12 Patents. She is the Placement Head of the Department of Information Technology, Head of the Entrepreneurship cell, Advisor of Amity IEEE student chapter (AICSC) and manages the funding and consultancy. She is a member of many international journals and conferences like Elsevier, IGI, Wiley, Inderscience and has reviewed many technical articles. She is a member of IETE, ACM, WEC (Women Entrepreneurship Cell), and other renowned technical societies and committees. She is a technical advisor at Deetya-Soft Pvt. Ltd. Noida, Ennoble Pvt. Ltd., MyDigital360, MSME Technology incubators, etc. She received government funding from the Ministry of Skill and Development for her project. She was awarded the "Faculty Innovation Excellence award 2019" on World Intellectual day by the secretary of the Department of science and technology, Government of India.

Table of Contents

1. Introduction and Tour of Various Tools of Predictive Analytics for Medical Science 2. Machine Learning Classification Algorithms for Prediction of Diseases 3. Biomedical Data Visualization and Data Representation 4. Classification and Clustering Algorithms for Medical Data 5. Optimized Data Retrieval and Data Storage for Health Care Application 6. Computational Intelligence System for Healthcare 7. High Performance Intelligent Systems for Real Time Medical Imaging 8. A Real-time Patient Health Monitoring System 9. Ensembled Convolutional Neural Network for Multi-class Skin Cancer Detection 10. Similarity Index Retrieval for School Kids' Sitting Posture Identification 11. Identification, Analysis and Recommendation of Sitting Posture of School Kids. 12. Fatty Liver Disease Prediction: Using Machine Learning Algorithms 13. Computer Aided Drug Design Case Study on Development of New Chemical Entities in the Management of HIV 14. Detection of Brain Tumor MRI Images using Comparison using Comprises on Analysis of Deep Learning Techniques 15. Biomedical Applications of Footprint Recognition: Harnessing Artificial Intelligence and Machine Learning for Footprint Image Monitoring