Topics of interest include theoretical and applied aspects of the:
- AI-based data augmentation techniques
- Surrogating methods for data augmentation
- Statistical learning in precision medicine
- Decision fusion for healthcare applications
- Semi-supervised learning applied to small data samples
- Graph signal processing in big data contexts
- Deep learning models in Healthcare and Biomedicine
- Ensemble learning for case of Small and Big data processing
- Bioinformatics for Healthcare applications
- Complex Health monitoring systems
- Analysis and prediction for Covid'19 data