and fairness in machine learning.Part II - computer vision: classification; and computer vision: 3D methods.Part III - computer vision: anomaly detection; and topics in computer vision.Part IV - brain-inspired computing;

.- Biosignal Processing in Medicine and Physiology. .- A deep learning multi-omics framework to combine microbiome and metabolome profiles for disease classification. .- CapsDA-Net: A Convolutional Capsule Domain Adversarial Neural Network for EEG-Based Attention  Recognition. .- ComplicaCode: Enhancing Disease Complication Detection in Electronic Health Records through ICD Path Generation. .- Depression detection based on multilevel semantic features. .- Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusion. .- Identify Disease-associated MiRNA-miRNA Pairs through Deep Tensor Factorization and Semi-supervised Learning. .- Interpretable EHR Disease Prediction System Based on Disease Experts and Patient Similarity Graph (DE-PSG). .- Meteorological Data based Detection of Stroke using Machine Learning Techniques. .- OFNN-UNI: Enhanced Optimized Fuzzy Neural Networks based on Unineurons for Advanced Sepsis Classification. .- ProTeM: Unifying Protein Function Prediction via Text Matching. .- SnoreOxiNet: Non-contact Diagnosis of Nocturnal Hypoxemia Using Cross-domain Acoustic Features. .- Unveiling the Potential of Synthetic Data in Sports Science: A Comparative Study of Generative Methods. .- Medical Image Processing. .- Adaptive Fusion Boundary-Enhanced Multilayer  Perceptual Network (FBAIM-Net) for Enhanced Polyp  Segmentation in Medical Imaging. .- Advancing Free-breathing Cardiac Cine MRI: Retrospective Respiratory Motion Correction Via Kspace-and-Image Guided Diffusion Model. .- Blood Cell Detection and Self-attention-based Mixed Attention Mechanism. .- CellSpot: Deep Learning-Based Efficient Cell Center Detection in Microscopic Images. .- Classification of dehiscence defects in titanium and zirconium dental implants. .- CurSegNet: 3D Dental Model Segmentation Network Based on Curve Feature Aggregation. .- DBrAL: A novel uncertainty-based active learning based on deep-broad learning for medical image classi cation. .- EDPS-SST: Enhanced Dynamic Path Stitching with Structural Similarity Thresholding for Large-Scale Medical Image Stitching under Sparse Pixel Overlap. .- Hop-Gated Graph Attention Network for ASD Diagnosis via PC-Based Graph Regularization Sparse Representation. .- MISS: A Generative Pre-training and Fine-tuning Approach for Med-VQA. .- MSD-HAM-Net: A Multi-modality Fusion Network of PET/CT Images for the Prognosis of DLBCL Patients. .- Multi-Modal Multi-Scale State Space Model for Medical Visual Question Answering. .- Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. .- Point-based Weakly Supervised 2.5D Cell Segmentation. .- Relative Local Signal Strength: the Impact of Normalization on the Analysis of Neuroimaging Data with Deep Learning. .- SCANet: Dual Attention Network for Alzheimer’s Disease Diagnosis Based on Gated Residual and Spatial Asymmetry Mechanisms. .- SCST: Spatial Consistent Swin Transformer for Multi-Focus Biomedical Microscopic Image Fusion. .- KnowMIM: a self-supervised pre-training framework based on knowledge-guided masked image modeling for retinal vessel segmentation. .- Transferability of Non-Contrastive Self-Supervised Learning to Chronic Wound Image Recognition. .- Two-stage Medical Image-text Transfer with Supervised Contrastive Learning.