.- AI for Desease.
.- Improving Early Sepsis Onset Prediction Through Federated Learning.
.- Experimenting Federated AI Models for Hematological Diseases.
.- Hearing Impairment Assessment in Infants through Explainable Computer Vision Analysis of Facial Features.
.- Type 2 Diabetes Prediction from multi-center Electronic Health Records in General Practice using Machine Learning.
.- Self-Attention as a Predictor of EEG Anomalies.
.- Cross-dataset Multivariate Time-series Model for Parkinson’s Diagnosis via Keyboard Dynamics.
.- Assessment and Compliance of Personalized Machine Learning Pharmacokinetic Models in the European Regulatory Environment.
.- Data Generation and Augmentation.
.- Knowledge Graph-Enhanced Retrieval-Augmented Generation for Nutrigenetics.
.- Generative Data Augmentation by Dataset Distillation.
.- Semantic Similarity in Radiology Reports via LLMs and NER.
.- From Scarce to Sufficient: Imaginary Image-like Features via Diffusion Models for Imbalanced Medical Data.
.- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks.
.- Multimodal Techniques.
.- Multimodal Machine Learning Architecture for Predictive Diagnosis and Treatment of Ophthalmic Diseases.
.- GNN-based Multimodal Analysis of Brain Anatomical and Functional Features for Parkinson’s Disease and Cognitive Decline Detection.
.- Data Donation for Digital Twins in Healthcare: Potential and Challenges in the European Context.
.- Image Segmentation.
.- Quality-Guided Focal Loss: Enhancing Minority Class Detection in Haematological Imaging.
.- Auto-prompting Foundation Models for Clinical Segmentation: The Case of Pathological Scapula.
.- Keynote Papers.
.- Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis.
.- Transcending the Annotation Bottleneck: AI-Powered Discovery in Biology and Medicine.
.- Increasing Data Availability Through Standardization: Unlocking AI in Digital Pathology.
.- Why accuracy isn’t enough. Rethinking Model Evaluation in Clinical AI with a user-centered utility metric.