Dancers and other performing artists are subject to head impacts that result in concussion-like symptoms. In spite of this, performing arts do not have access to the continual, focused emphasis on the diagnosis, management, and prevention of concussions that is commonplace in sports. Performing arts present a unique environment in which concussions occur and must be managed. This article outlines what is known about performing arts concussions, describes mechanisms of head impacts sustained by participants in dance and the related artforms of theater, circus, and film and television stunts, and offers concussion management guidelines for these artistic fields.
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http://dx.doi.org/10.1016/j.pmr.2020.09.007 | DOI Listing |
Support Care Cancer
January 2025
Department of Nursing, Nanfang Hosptial of Southern Medical University, Guangzhou, 510515, People's Republic of China.
Purpose: Our study aim was to understand the (human and organizational) factors influencing fall risk among people with hematological malignancies using the Reason model as a framework, providing insights that can inform the development of safe and effective fall management strategies.
Methods: Purposive sampling was employed to conduct semi-structured interviews with 13 people with hematological malignancies and 12 nurses from the hematology department of a tertiary grade A hospital in Guangzhou from December 2023 to February 2024. The topic analysis method was utilized to analyze the interview data.
J Imaging Inform Med
January 2025
Computer Science Department, University of Geneva, Geneva, Switzerland.
Accurate wound segmentation is crucial for the precise diagnosis and treatment of various skin conditions through image analysis. In this paper, we introduce a novel dual attention U-Net model designed for precise wound segmentation. Our proposed architecture integrates two widely used deep learning models, VGG16 and U-Net, incorporating dual attention mechanisms to focus on relevant regions within the wound area.
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January 2025
School of Design, Hunan University, Changsha, 410082, China. Electronic address:
The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to localize myocardial infarction (MI) that is characterized by abnormal waveform patterns on the ECG. MI is a serious cardiovascular disease, and accurate, timely diagnosis is crucial for preventing severe outcomes. Current ECG analysis methods mainly rely on intra- and inter-lead feature extraction, but most models overlook the medical knowledge relevant to disease diagnosis.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
College of Information Science and Engineering, Northeastern University, China.
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental methods, accurate computational approaches for protein-protein interaction sites (PPIS) prediction can save significant time and costs.
View Article and Find Full Text PDFComput Methods Programs Biomed
January 2025
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, PR China. Electronic address:
Background And Objective: Atrial fibrillation (AF) is a significant cause of life-threatening heart disease due to its potential to lead to stroke and heart failure. Although deep learning-assisted diagnosis of AF based on ECG holds significance in clinical settings, it remains unsatisfactory due to insufficient consideration of noise and redundant features. In this work, we propose a novel multiscale feature-enhanced gating network (MFEG Net) for AF diagnosis.
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