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
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1. Ontology-based Process for Unstructured Medical Report Mapping 2. A Computer-aided Diagnoses System for Detecting Multiple Ocular Diseases Using Color Retinal Fundus Images 3. A DEFS based System for Differential Diagnosis between Severe Fatty Liver and Cirrhotic Liver using Ultrasound Images 4. Infrared Thermography and Soft Computing for Diabetic Foot Assessment 5. Automated Classification of Hypertension and Coronary Artery Disease Patients by PNN, KNN and SVM Classifiers using HRV Analysis 6. Optimization of ROI Size for Development of Computer Assisted Framework for Breast Tissue Pattern Characterization using Digitized Screen Film Mammograms 7. Optimization of ANN architecture: A review on nature-inspired techniques 8. Ensemble Learning Approach to Motor-Imagery EEG Signal Classification 9. Medical Images Analysis Based on Multi-Label Classification Methods 10. Figure Search in Biomedical Domain: A Survey of Techniques and Challenges 11. Application of Machine Learning Algorithms for Classification and Security of Diagnostic Images 12. Robotics in Healthcare: An Internet of Medical Robotic Things (IoMRT) Perspective
Dr. Nilanjan Dey is an Asst. Professor in the Department of Information Technology in Techno India College of Technology,
Rajarhat, Kolkata, 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 OfSgientifig and Engineering Unions, Bulgaria, Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. 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, and the International Journal of Synthetic Emotions (IJSE), IGI Global, US. He is
Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International
Journal of Image Mining (IJIM), Inderscience, Regional Editor-Asia of International Journal of Intelligent Engineering
Informatics (IJIEI), Interscience and Associated Editor of International Journal of Service Science, Management, Engineering,
and Technology, IGI Global. His research interests include Medical Imaging, Soft computing, Data mining, Machine learning,
Rough set, Mathematical Modeling and Computer Simulation, Modeling of Biomedical Systems, Robotics and Systems,
Information Hiding, Security, Computer Aided Diagnosis, and Atherosclerosis. He has published a dozen books and more than
200 international conferences and journal papers. He is a life member of IE, UACEE, and ISOC.
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.
Ashour, Amira S.
Amira S. Ashour is an Assistant Professor and Head of Electronics and Electrical Communications Engineering Department, Faculty of Engineering, Tanta University, Egypt. She is a member in the Research and Development Unit, Faculty of Engineering, Tanta University, Egypt. She received the B.Eng. degree in Electrical Engineering from Faculty of Engineering, Tanta University, Egypt in 1997, M.Sc. in Image Processing in 2001 and Ph.D. in Smart Antenna in 2005 from Faculty of Engineering, Tanta University, Egypt. Ashour has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the vice chair of CS department, CIT college, Taif University, KSA for 5 years. Her research interests are Smart antenna, Direction of arrival estimation, Targets tracking, Image processing, Medical imaging, Machine learning, Biomedical Systems, Pattern recognition, Image analysis, Computer vision, Computer-aided detection and diagnosis systems, Optimization, and Neutrosophic theory. She has 15 books and about 150 published journal papers. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US.
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.