A FAIR hyperontology is developed that semantically integrates and harmonizes clinical, biological, and imaging metadata and data spread across disparate sources, and captures and accurately represents oncology and medical imaging.
M. El Ghosh, Varvara Kalokyri, M. Bobowicz et al.· Journal of Medical Internet...· 0 citations
The results show that DG methods, particularly those that explicitly regularize the learning process, improve out-of-domain generalization, but do not fully close the gap with in-domain performance, underscore the necessity of incorporating DG strategies to develop clinically deployable AI models.
D. Pulido-Arias, Mason C. Cleveland, Jay B. Patel et al.· Journal of imaging informati...· 0 citations
B baseline performance is established using an R(2+1)D video backbone with LSTM aggregation trained from Kinetics-400 pretrained weights, demonstrating strong discriminative performance for cardiac functional assessment and LV dysfunction classification, while early cardiotoxicity prediction from a single pre-therapy v...
G. Kalliatakis, G. Karanasiou, Georgios C. Manikis et al.· 1 citation
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