Decision making in case of medical diagnosis is a complicated process. A large number overlapping structures and cases, distractions, tiredness, limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed assist clinicians overcoming these informed correct decisions disease Many academic papers involving use machine for increasi...

Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the closeness of cross-domain centroids. However, inner-class compactness and underlying fine-grained subtype structure remained largely underexplored. In this work, we propose to adaptively carry out subtype-aware align...