Federated and Continual Learning have emerged as potential paradigms for...
Access to the proper infrastructure is critical when performing medical ...
Automatic segmentation of ground glass opacities and consolidations in c...
Most continual learning methods are validated in settings where task
bou...
In clinical settings, where acquisition conditions and patient populatio...
Calibration and uncertainty estimation are crucial topics in high-risk
e...
Limited amount of labelled training data are a common problem in medical...
Federated Learning is the most promising way to train robust Deep Learni...
The recent achievements of Deep Learning rely on the test data being sim...
Deep learning for medical imaging suffers from temporal and privacy-rela...
Automatic segmentation of lung lesions in computer tomography has the
po...
Continual learning protocols are attracting increasing attention from th...
M3d-CAM is an easy to use library for generating attention maps of CNN-b...