Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented.

The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers.

• Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging
• Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining
• Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

About the Authors

Nilanjan Dey received his Ph. D. Degree from Jadavpur University, India, in 2015. He is an Assistant Professor in the Department of Information Technology, Techno International New Town, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, Bulgaria. Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. His research topic is Medical Imaging, Data mining, Machine learning, Computer Aided Diagnosis, Atherosclerosis etc. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IGI Global), US, (Co-EinC) and International Journal of Natural Computing Research (IGI Global), US. Series Editor (Co.) of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier, Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He has 20 books and more than 200 research articles in peer-reviewed journals and international conferences. He is the organizing committee member of several international conferences including ITITS, W4C, ICMIR, FICTA, ICICT.

Surekha Borra is currently a Professor in the Department of ECE, K. S. Institute of Technology, Bangalore, India. She earned her Doctorate in Image Processing from Jawaharlal Nehru Technological University, Hyderabad, India, in 2015. Her research interests are in the areas of Image and Video Analytics, Machine Learning, Biometrics and Remote Sensing. She has published 1 edited book, 8 book chapters and 22 research papers to her credit in refereed & indexed journals, and conferences at international and national levels. Her international recognition includes her professional memberships & services in refereed organizations, programme committees, editorial & review boards, wherein she has been a guest editor for 2 journals and reviewer for journals published by IEEE, IET, Elsevier, Taylor & Francis, Springer, IGI-Global etc,. She has received Woman Achiever's Award from The Institution of Engineers (India), for her prominent research and innovative contribution (s)., Woman Educator & Scholar Award for her contributions to teaching and scholarly activities, Young Woman Achiever Award for her contribution in Copyright Protection of Images.

Amira S. Ashour is currently an Assistant Professor and Head of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Egypt. She was the Chair of Computer Engineering Department- female section, Computers and Information Technology (CIT) College, Taif University, KSA for one year from 2015. She was the Chair of Computer Science Department - female section, CIT College, Taif University, KSA for 5 years. She has authored/edited more than 20 books with Elsevier, and Springer, and published more than 150 papers in repute journals.

Ashour is a Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US. She is an Associate Editor and reviewer in several journals. Her research interests include Biomedical Engineering, Computer- aided diagnosis systems, Image processing, Medical imaging, Machine learning, Optimization, Neutrosophic theory, Smart antenna, Direction of arrival estimation, and Targets tracking.

Fuqian Shi, is in an Visiting Associate Professor, University of Central Florida Fuzzy Sets, Rough Sets, Industrial Design. He has got the best paper award, the 14th natural science best papers of Wenzhou City, 2009-2010. He has more than 40 publications in international journals. He reviewed several works for the IEEE Transactions Fuzzy Systems, the International Journal of System Dynamics Applications and others. He is in the Editorial Review Board, International Journal of System Dynamics Applications (IJSDA), and the Electrotechnics, Electronics, Automatic Control and Computer Science Series.