Chinese Medical Named Entity Recognition (CMNER) seeks to identify and extract medical entities from unstructured medical texts. Existing methods often depend on single-modality representations and fail to fully exploit the complementary nature of di...
Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial for improving patients' survival outcomes. In this paper, we propose to employ convolutional neural networks to model the non-linear relationship bet...
Rationale Integrating artificial intelligence (AI) into education has introduced transformative possibilities, particularly through adaptive learning systems. Rehabilitation science education stands to benefit significantly from the integration of AI...
To enhance the adaptability of tree-climbing robots to changes in tree diameter and load capacity, an "I-shaped" pneumatic flexible tree - climbing robot was designed using self-developed pneumatic flexible joints and retractable needle anchors. The ...
Developing vaccines with a better stability is an area of improvement to meet the global health needs of preventing infectious diseases. With the advancement of data science and artificial intelligence, innovative approaches have emerged. This manusc...
Recent advances in experimental methods have enabled researchers to collect data on thousands of analytes simultaneously. This has led to correlational studies that associated molecular measurements with diseases such as Alzheimer's, Liver, and Gastr...
BACKGROUND: Overcrowding and long wait times in emergency departments (EDs) remain global challenges that negatively affect patient outcomes and staff satisfaction. As an emerging technology, artificial intelligence (AI) offers the potential to optim...
OBJECTIVE: To systematically evaluate large language models (LLMs) for automated information extraction from gastroscopy and colonoscopy reports through prompt engineering, addressing their ability to extract structured information, recognize complex...
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where, despite treatment, they continue to experience significant burden. We sought to develop a tool c...
The Spiking Neural Network (SNN) is a third-generation neural network recognized for its energy efficiency and ability to process spatiotemporal information, closely imitating the behavioral mechanisms of biological neurons in the brain. SNN exhibit ...
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