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Non-Stationary and Nonlinear Data Processing for Automated Computer-Aided Medical Diagnosis

Non-Stationary and Nonlinear Data Processing for Automated Computer-Aided Medical Diagnosis

          
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About the Book

Non-Stationary and Nonlinear Data Processing for Automated Computer-Aided Medical Diagnosis demonstrates the applications of machine learning and deep learning combined with signal processing techniques for human-machine interface applications using EMG signals. The book includes the analysis and classification of various heart diseases based on bio-signals like electrocardiogram (ECG), photoplethysmography (PPG), and phonocardiogram (PCG) signals. Various machine learning approaches, including advanced algorithms like multivariate signal processing, time-frequency analysis, and nonlinear signal processing are covered for CAD of neural, muscular, and cardiovascular diseases. The methods for CAD of various brain disorders are also included. Presented techniques utilize advanced non-stationary and nonlinear signal processing, along with machine learning and deep learning-based classification processes. CAD methods for diagnosing various neurological diseases are based on bio-signals such as electroencephalogram (EEG) and magnetoencephalogram (MEG), as well as medical images like magnetic resonance imaging (MRI) and computerized tomography (CT). Finally, the book addresses various types of medical signals and images, integrating nonlinear and non-stationary signal processing, machine learning, and deep learning within the CAD framework for diagnosing various diseases.

Table of Contents:
1. Introduction to Computer-Aided Medical Diagnosis Systems 2. Advanced Signal Processing and Machine Learning Techniques 3. EEG-Based Imagined Speech Recognition for Brain-Computer Applications 4. Automated Emotion Detection Using Multi-Modal Data 5. Visual Cognitive Systems Using EEG and MEG for BCI Applications 6. ECG Sensor-Based Devices for Cardiac Disease Diagnosis 7. Automated Detection of Neurological Disorders via Voiced Speech Patterns 8. EEG-Based Diagnosis Systems for Sleep Disorders 9. Automated Brain Cancer Diagnosis Using MRI 10. Automated Eye Disease Diagnosis Using Ophthalmoscopic Images 11. PPG-Based Diagnosis System for Cardiovascular Disorders 12. EMG Signal-Based Devices for Neuromuscular Diseases 13. Wearable Systems for Real-Time Disease Diagnosis and Predictive Analytics 14. Computer-Aided Detection of Thoracic Diseases Using X-Ray Images 15. Computer-Aided Detection of Kidney Diseases Using Ultrasound Images 16. IoT-Enabled Diagnosis System for Telemedicine Applications


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Product Details
  • ISBN-13: 9780443314261
  • Publisher: Elsevier Science Publishing Co Inc
  • Publisher Imprint: Academic Press Inc
  • Height: 235 mm
  • No of Pages: 422
  • Width: 191 mm
  • ISBN-10: 0443314268
  • Publisher Date: 01 Jun 2026
  • Binding: Paperback
  • Language: English
  • Weight: 450 gr


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