Part I: Biomedical Applications of Computational Intelligence Techniques
Bilattice CADIAG-II: Theory and Experimental Results
A Combination Model of Robust Principal Component Analysis and Multiple Kernel Learning for Cancer Patient Stratification
Attention U-Net with Active Contour based Hybrid Loss for Brain Tumor Segmentation
Refining Skip Connections by Fusing Multi-scaled Context in Neural Network for Cardiac MR Image Segmentation
End-to-end Hand Rehabilitation System with Single-shot Gesture Classification for Stroke Patients
Feature Selection based on Shapley Additive Explanations on Metagenomic Data for Colorectal Cancer Diagnosis
Clinical Decision Support Systems for Pneumonia Diagnosis using Gradient-weighted Class Activation Mapping and Convolutional Neural Networks
Improving 3D Hand Pose Estimation with Synthetic RGB Image Enhancement using RetinexNet and Dehazing
Imbalance in Learning Chest X-ray Images for COVID-19 Detection
Deep Learning based COVID-19 Diagnosis by Joint Classifation and Segmentation
Part II: General Computational Intelligence Techniques and Their Applications
Why It Is Sufficient to Have Real-Valued Amplitudes in Quantum Computing.