Main description:

Covers computational Intelligence techniques like fuzzy sets, artificial neural networks, deep neural networks, and genetic algorithm for Healthcare systems
Provides easy understanding concepts like signal and image filtering techniques
Includes discussion over filtering and classification problems
Details studies with medical signal (ECG, EEG, EMG) and image (X-rays, FMRI, CT) datasets
Describes evolution parameters such as signal-to-noise ratio, mean square error, accuracy, precision, and recall

Contents:

1. A Survey of Machine Learning in Healthcare. 2. A Review on Biomedical Signals with Fundamentals of Digital Signal Processing. 3. Images in Radiology : Concepts of Image Acquisition and the Nature of Images. 4. Fundamentals of Artificial Intelligence and Computational Intelligence Techniques with their Applications in Healthcare Systems. 5. Machine Learning Approach with Data Normalization Technique for Early Stage Detection of Hypothyroidism. 6. GPU-based Medical Image Segmentation: Brain MRI Analysis Using 3D Slicer. 7. Preliminary Study of Retinal Lesions Classification on Retinal Fundus Images for The Diagnosis of Retinal Diseases. 8. Automatic Screening of COVID-19 based on CT Scan Images through Extreme Gradient Boosting. 9. Investigations on Convolutional Neural Network in Classification of the Chest X-Ray Images for COVID-19 and Pneumonia. 10. Improving the Detection of Abdominal and Mediastinal Lymph Nodes in CT Images Using Attention U-Net Based Deep Learning Model. 11. Swarm Optimized Hybrid Layer Decomposition and Reconstruction Model for Multi-Modal Neurological Image Fusion. 12. Hybrid Seeker Optimization Algorithm-Based Accurate Image Clustering for Automatic Psoriasis Lesion Detection. 13. A COVID-19 Tracker for Medical Front-Liners. 14. Implementation of One Dimensional Convolutional Neural Network for ECG Classification on Python. 15. Pneumonia Detection from X-ray Images by Two Dimensional Convolutional Neural Network on Python Platform.