Artificial Intelligence in Biomedical and Modern Healthcare Informatics

Texte du rabat

AI in Biomedical and Modern Healthcare Informatics provide a deeper understanding of current trends in AI and machine learning within health care diagnosis. Its practical approach in healthcare gives insight into wearable sensors and device modules to help doctors and their patients in enhanced healthcare systems. The book helps readers detect common difficulties and their solutions for early detection and prediction of any disease. In 34 chapters AI in Biomedical and Modern Healthcare Informatics provides beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications. With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare

Contenu

1. Fundamentals of EEG signal Processing
   
   2. Review on EEG signal modelling and analysis
   3. EEG signal Modelling
   4. Signal Transforms and joint time frequency analysis
   5. Classification and clustering of Brain signals
   6. Blind and Semi-Blind Source Separation
   7. Connectivity of Brain Regions
   8. Detection and Tracking of Event Related Potentials
   9. Emotion Encoding, Regulation and Control
   10. Sleep and Sleep Apnoea
   11. Brain-Computer Interfacing
   12. EEG and MEG Source localization
   13. Seizure and Epilepsy
   14. Computed Tomography Imaging and Angiography: Principles
   15. Characterization of biomedical signals: Feature engineering and extraction
   16. Supervised and unsupervised learning: Machine learning in biomedical signal processing with ECG applications
   17. Deep EEG: Deep learning in biomedical signal processing with EEG applications
   18. Fuzzy logic in medicine
   19. Neural network applications in medicine
   20. Analysis and management of sleep data
       21.Ontology-based Process for Unstructured Medical Report Mapping
   21. A Computer-aided Diagnoses System for Detecting Multiple Ocular Diseases Using Color Retinal Fundus Images
   22. A DEFS based System for Differential Diagnosis between Severe Fatty Liver and Cirrhotic Liver using Ultrasound Images
   23. Infrared Thermography and Soft Computing for Diabetic Foot Assessment
   24. Automated Classification of Hypertension and Coronary Artery Disease Patients by PNN, KNN and SVM Classifiers using HRV Analysis
   25. Optimization of ROI Size for Development of Computer Assisted Framework for Breast Tissue Pattern Characterization using Digitized Screen Film Mammograms
   26. Optimization of ANN architecture: A review on nature-inspired techniques
   27. Ensemble Learning Approach to Motor-Imagery EEG Signal Classification
   28. Medical Images Analysis Based on Multi-Label Classification Methods
   29. Figure Search in Biomedical Domain: A Survey of Techniques and Challenges
   30. Application of Machine Learning Algorithms for Classification and Security of Diagnostic Images
   31. Bio signals analysis (heart, phonatory system, and muscles)
   32. EEG-based subject identification with multi-class classification
   33. Trends and applications of ECG analysis and classification