Automated medical image classification is the key component in intellige...
Current deep learning models often suffer from catastrophic forgetting o...
Graph neural networks (GNNs) have recently emerged as a promising learni...
Data imbalance between common and rare diseases during model training of...
Imbalanced training data is a significant challenge for medical image
cl...
Accurate automated analysis of electroencephalography (EEG) would largel...
Ensemble learning is a classical learning method utilizing a group of we...
Continually learning to segment more and more types of image regions is ...
This paper represents the first effort to explore an automated architect...
Deep learning models have shown their superior performance in various vi...
Successful continual learning of new knowledge would enable intelligent
...
Continual learning of new knowledge over time is one desirable capabilit...
White matter hyperintensities (WMH) are commonly found in the brains of
...