Most of the modern natural language processing (NLP) techniques are based on the vector space models of language, in which each word is represented by a vector in a high dimensional space. One of the earliest successes was demonstrated by the four-te...
Neural networks : the official journal of the International Neural Network Society
Oct 18, 2024
Few-Shot Semantic Segmentation (FSS) aims to tackle the challenge of segmenting novel categories with limited annotated data. However, given the diversity among support-query pairs, transferring meta-knowledge to unseen categories poses a significant...
Document-level relation triplet extraction is crucial in biomedical text mining, aiding in drug discovery and the construction of biomedical knowledge graphs. Current language models face challenges in generalizing to unseen datasets and relation typ...
With the acceleration of urbanization, bridges, as crucial infrastructure, their structural health and stability are paramount to public safety. This paper proposes Mamba-Enhanced HRNet for bridge damage detection. Mamba-Enhanced HRNet integrates the...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 16, 2024
Medical image segmentation is a crucial component of computer-aided clinical diagnosis, with state-of-the-art models often being variants of U-Net. Despite their success, these models' skip connections introduce an unnecessary semantic gap between th...
Neural networks : the official journal of the International Neural Network Society
Oct 15, 2024
Long-tailed data distributions have been a major challenge for the practical application of deep learning. Information augmentation intends to expand the long-tailed data into uniform distribution, which provides a feasible way to mitigate the data s...
Coronary artery disease (CAD) is one of the leading causes of death worldwide. Accurate extraction of individual arterial branches from invasive coronary angiograms (ICA) is critical for CAD diagnosis and detection of stenosis. Generating semantic se...
Journal of applied clinical medical physics
Oct 10, 2024
PURPOSE/AIM: This paper provides a pedagogical example for systematic machine learning optimization in small dataset image segmentation, emphasizing hyperparameter selections. A simple process is presented for medical physicists to examine hyperparam...
Neural networks : the official journal of the International Neural Network Society
Oct 9, 2024
Entity linking, the process of connecting textual mentions in documents to canonical entities within a knowledge base, plays an integral role in a myriad of natural language processing tasks. A significant challenge prevalent within the field is the ...
OBJECTIVE: This study investigates the use of Large Language Models (LLMs) for matching patients to clinical trials (CTs) within an information retrieval pipeline. Our objective is to enhance the process of patient-trial matching by leveraging the se...