Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for w...
IEEE journal of biomedical and health informatics
Oct 5, 2023
Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the mo...
DNA methylation is a crucial topic in bioinformatics research. Traditional wet experiments are usually time-consuming and expensive. In contrast, machine learning offers an efficient and novel approach. In this study, we propose DeepMethylation, a no...
Human pose estimation is the basis of many downstream tasks, such as motor intervention, behavior understanding, and human-computer interaction. The existing human pose estimation methods rely too much on the similarity of keypoints at the image feat...
Journal of chemical information and modeling
Aug 29, 2023
Plant small secretory peptides (SSPs) play an important role in the regulation of biological processes in plants. Accurately predicting SSPs enables efficient exploration of their functions. Traditional experimental verification methods are very reli...
Computer methods and programs in biomedicine
Aug 25, 2023
BACKGROUND AND OBJECTIVE: Accurate object segmentation in medical images is a crucial step in medical diagnosis and other applications. Despite years of research on automatic segmentation approaches, achieving clinically acceptable image quality rema...
Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they provide a wealth of information about gene expression at the cell level, ...
Proceedings of the National Academy of Sciences of the United States of America
Jul 31, 2023
Transformer neural networks have revolutionized structural biology with the ability to predict protein structures at unprecedented high accuracy. Here, we report the predictive modeling performance of the state-of-the-art protein structure prediction...
The US Food and Drug Administration (FDA) regulatory process often involves several reviewers who focus on sets of information related to their respective areas of review. Accordingly, manufacturers that provide submission packages to regulatory agen...
Deep learning-based medical image segmentation has made great progress over the past decades. Scholars have proposed many novel transformer-based segmentation networks to solve the problems of building long-range dependencies and global context conne...
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