2 papers
cs.CV2026
SMILE: Self-Explainable Multimodal Information Bottleneck for Medical Diagnosis
Yuqing Yang, Alexander Schmatz, Zhaozhao Ma +3
Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Most existing explainability m…
eess.IV2025
Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Jakub Frac, Alexander Schmatz, Qiang Li +2
Functional magnetic resonance imaging (fMRI) analysis faces significant challenges due to limited dataset sizes and domain variability between studies. Traditional self-supervised…