Intelligent Data Analysis for Biomedical Applications. Intelligent Data-Centric Systems: Sensor Collected Intelligence

  • ID: 4593670
  • Book
  • 450 Pages
  • Elsevier Science and Technology
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Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases.

  • Provides the methods and tools necessary for intelligent data analysis and gives solutions to problems resulting from automated data collection
  • Contains an analysis of medical databases to provide diagnostic expert systems
  • Addresses the integration of intelligent data analysis techniques within biomedical information systems
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1. A Review on Intelligent Data Analysis System for an IoT-Based Capsule Endoscopy System
2. Ant Colony optimization-based image texture segmentation in medical images
3. A Feature Fusion Based Discriminant Learning Model for Diagnosis of Neuromuscular Disorders Using Single Channel Needle EMG Signal
4. Evolution of Consciousness Systems with bacteria
5. Analysis of transform-based compression techniques for MRI and CT images
6. Liveness Assured Multimodal Biometrics using Electrocardiogram for Smart Health Applications
7. Medical Image Retrieval System in PACS Environment for Clinical Decision Making
8. A Neuro Fuzzy Inference Model for Diabetic Retinopathy Classification
9. Predictive Analysis of breast cancer using machine learning techniques
10. Right Ventricle Image Segmentation from MRI using optimization techniques
11. Computational Automated System for Red Blood Cell Detection and Segmentation
12. Fuzzy logic based approaches for gene regulatory network inference
13. Evolutionary Algorithm with Memetic Search for Optic Disc Localization in Retinal Fundus Images
14. A novel approach of targeting prognostics of Bruxism disorder using C4-P4 channel of EEG signal
15. Physiotherapy and Rehabilitation Assessment System Using Bio-inspired Visual Cortex Computational Model
16. Classification of Myocardial Ischemia in Contrast Enhancement Using Machine Learning
17. Simple link sensor network based remote monitoring of multiple patients
18. Prognosticating the risk of fibrosis progression in non-alcoholic fatty liver diseases
19. Alzheimer Disease Detection from Structural MR Images using Fuzzy C-Means based Deep Belief Neural Network
20. Optimal Control of Fractional Order HIV-Immune System Using Neural Network Approach
21. Diagnosis of Ocular Disease using Optical Coherence Tomography Image
22. Hybrid Approach for Classification of EEG Signals using T-F Images with Wavelets and Texture Features
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Hemanth, D. Jude
Dr. D. Jude Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. His research areas include Computational Intelligence and Image processing. He has authored more than 100 research papers in reputed International Journals such as Neurocomputing, Neural Computing and Applications, Neural Network World, etc. He has authored one book with (VDM-Verlag, Germany) and many book chapters with reputed publishers such as Springer and Inderscience. He is the guest editor of the book series "Lecture Notes in Computational Vision and Biomechanics” with Springer and "Advances in Parallel Computing” with IOS Press. He has been serving as Associate editor of various International Journals with Publishers such as IEEE (IEEE Access Journal), Springer (Sensing and Imaging), Inderscience (IJAIP, IJICT, IJCVR, IJBET), IOS Press (Intelligent Decision Technologies), and others.
Gupta, Deepak
He has completed his B.Tech. from Guru Gobind Singh Indraprastha University, M.E. from Delhi College of Engineering (Now Delhi Technological University) and has submitted his Ph.D. thesis. He has published 24 text books on various topics of computer science and engineering with International Publishers, has edited one book published by Lambert Academic Publisher (LAP) Germany and 18 research papers in various International Journals, indexed with SCIE, Scopus, ESCI, DBLP, WoS Journals and International Conferences. His research areas include Human-Computer Interaction, Artificial Intelligence, Soft Computing, Bio-Inspired Algorithms, Data Mining.
Emilia Balas, Valentina
Valentina E. Balas holds a Ph.D. in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 250 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in-Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), Editorial Board member of several national and international journals and is evaluator expert for national and international projects. Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad and was Vice-president (Awards) of IFSA International Fuzzy Systems Association Council (2013-2015) and is a Joint Secretary of the Governing Council of Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, India.
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