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1. Classıfıcatıon of Unhealthy and Healthy Neonates in Neonatal Intensıve Care Unıts Usıng Medıcal Thermography Processıng and Artıfıcıal Neural Network
2. Use of Health-related Indices and Cassification Methods in Medical Data
3. Image Analysis for Diagnosis and Early Detection of Hepatoprotective Activity
4. Characterization of Stuttering Dysfluencies using Distinctive Prosodic and Source Features
5. A Deep Learning Approach for Patch-based Disease Diagnosis from Microscopic Images
6. A Breast Tissue Characterization Framework Using PCA and Weighted Score Fusion of Neural Network Classifiers
7. Automated Arrhythmia Classification for Monitoring Cardiac Patients Using Machine Learning Techniques
8. IoT-based Fluid and Heartbeat Monitoring For Advanced Healthcare
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.
- Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges
- Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications
- Introduces several techniques for medical image processing and analysis for CAD systems design
Biomedical engineers and researchers in data analytics, soft computing, deep learning, and computer-aided diagnosis systems
- No. of pages:
- © Academic Press 2019
- 31st July 2019
- Academic Press
- Paperback ISBN:
- eBook ISBN:
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.
Assistant Professor, Department of Information Technology, Techno International New Town, Kolkata, India