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Patients with anterior cruciate ligament reconstruction frequently present asymmetries in the sagittal plane dynamics when performing single leg jumps but their assessment is inaccessible to health-care professionals as it requires a complex and expensive system. With the development of deep learning methods for human pose detection, kinematics can be quantified based on a video and this study aimed to investigate whether a relatively simple 2D multibody model could predict relevant dynamic biomarkers based on the kinematics using inverse dynamics. Six participants performed ten vertical and forward single leg hops while the kinematics and the ground reaction force "GRF" were captured using an optoelectronic system coupled with a force platform.
View Article and Find Full Text PDFAlzheimer's disease image classification based on enhanced residual attention network.
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January 2025
School of Emergency Management, Institute of Disaster Prevention, Sanhe, Hebei, China.
With the increasing number of patients with Alzheimer's Disease (AD), the demand for early diagnosis and intervention is becoming increasingly urgent. The traditional detection methods for Alzheimer's disease mainly rely on clinical symptoms, biomarkers, and imaging examinations. However, these methods have limitations in the early detection of Alzheimer's disease, such as strong subjectivity in diagnostic criteria, high detection costs, and high misdiagnosis rates.
View Article and Find Full Text PDFDual-hybrid intrusion detection system to detect False Data Injection in smart grids.
PLoS One
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.
View Article and Find Full Text PDFEnhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions.
PLoS One
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School of Business Economics, European Union University, Montreux, Switzerland.
As people's material living standards continue to improve, the types and quantities of household garbage they generate rapidly increase. Therefore, it is urgent to develop a reasonable and effective method for garbage classification. This is important for resource recycling and environmental improvement and contributes to the sustainable development of production and the economy.
View Article and Find Full Text PDFDeep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma.
PLoS One
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Department of Pathology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background: Ras-GTPase-activating protein (GAP)-binding protein 1 (G3BP1) emerges as a pivotal oncogenic gene across various malignancies, notably including nasopharyngeal carcinoma (NPC). The use of automated image analysis tools for immunohistochemical (IHC) staining of particular proteins is highly beneficial, as it could reduce the burden on pathologists. Interestingly, there have been no prior studies that have examined G3BP1 IHC staining using digital pathology.
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