Biomedical relation extraction has long been considered a challenging task due to the specialization and complexity of biomedical texts. Syntactic knowledge has been widely employed in existing research to enhance relation extraction, providing guida...
OBJECTIVE: Biomedical Named Entity Recognition (bio NER) is the task of recognizing named entities in biomedical texts. This paper introduces a new model that addresses bio NER by considering additional external contexts. Different from prior methods...
Journal of imaging informatics in medicine
Jun 10, 2024
To develop a robust segmentation model, encoding the underlying features/structures of the input data is essential to discriminate the target structure from the background. To enrich the extracted feature maps, contrastive learning and self-learning ...
Neural networks : the official journal of the International Neural Network Society
Jun 10, 2024
Few-shot image classification involves recognizing new classes with a limited number of labeled samples. Current local descriptor-based methods, while leveraging consistent low-level features across visible and invisible classes, face challenges incl...
Neural networks : the official journal of the International Neural Network Society
Jun 7, 2024
This paper proposes a novel approach to semantic representation learning from multi-view datasets, distinct from most existing methodologies which typically handle single-view data individually, maintaining a shared semantic link across the multi-vie...
International journal of computer assisted radiology and surgery
Jun 7, 2024
OBJECTIVES: In patients having naïve glioblastoma multiforme (GBM), this study aims to assess the efficacy of Deep Learning algorithms in automating the segmentation of brain magnetic resonance (MR) images to accurately determine 3D masks for 4 disti...
Neural networks : the official journal of the International Neural Network Society
Jun 4, 2024
In overcoming the challenges faced in adapting to paired real-world data, recent unsupervised single image deraining (SID) methods have proven capable of accomplishing notably acceptable deraining performance. However, the previous methods usually fa...
Deep Neural Networks (DNNs) based semantic segmentation of the robotic instruments and tissues can enhance the precision of surgical activities in robot-assisted surgery. However, in biological learning, DNNs cannot learn incremental tasks over time ...
Neural networks : the official journal of the International Neural Network Society
Jun 1, 2024
In natural language processing, fact verification is a very challenging task, which requires retrieving multiple evidence sentences from a reliable corpus to verify the authenticity of a claim. Although most of the current deep learning methods use t...
Neural networks : the official journal of the International Neural Network Society
May 31, 2024
The demand for "online meetings" and "collaborative office work" keeps surging recently, producing an abundant amount of relevant data. How to provide participants with accurate and fast summarizing service has attracted extensive attention. Existing...