LabCora is proposed, a novel framework for semi-supervised multi-label medical image classification that mitigates confirmation bias by explicitly modeling label correlations and using them to correct unreliable pseudo-labels and a Cross-Domain Adversarial module is introduced to alleviate the distribution mismatch via...
Yi Zhong, Zhi-Qiang Shen, Peng Cao et al.· Medical and Biological Engin...· 0 citations
KD-Brain is proposed, a Prior-Informed Graph Learning framework for explicitly encoding prior knowledge to guide the learning process, which design a Semantic-Conditioned Interaction mechanism that injects semantic priors into the attention query, explicitly navigating the subnetwork interactions based on their functio...
Siyu Liu, Guang-Qi Wen, Peng Cao et al.· arXiv.org· 0 citations
Speech-based mental disorder screening (SMS) is hindered by the scarcity of labeled training data. Although self-supervised learning (SSL) can alleviate this limitation by leveraging unlabeled speech, the general representations learned by existing SSL methods often contain unhelpful redundancies and are not well adapt...
Wen-Ju Yang, Yu-Hao Cao, Juan Liu et al.· IEEE journal of biomedical a...· 0 citations
ReMatch is introduced, a segmentation-synthesis co-training framework for semi-supervised domain generalization in medical image segmentation that Synthesizes unlabeled images with both high semantic consistency and style diversity by leveraging Texture and Shape features derived from the segmentation process.
Zhi-Qiang Shen, Qing-Shan Hou, Peng Cao et al.· Artif. Intell. Medicine· 0 citations
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