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Draw+: network-based computational drug repositioning with attention walking and noise filtering.
Health Inf Sci Syst
December 2025
Division of Software, Yonsei University, Mirae Campus, Yeonsedae-gil 1, Wonju-si, 26493 Gangwon-do Korea.
Purpose: Drug repositioning, a strategy that repurposes already-approved drugs for novel therapeutic applications, provides a faster and more cost-effective alternative to traditional drug discovery. Network-based models have been adopted by many computational methodologies, especially those that use graph neural networks to predict drug-disease associations. However, these techniques frequently overlook the quality of the input network, which is a critical factor for achieving accurate predictions.
View Article and Find Full Text PDFA novel multi-level 3D pose estimation framework for gait detection of Parkinson's disease using monocular video.
Front Bioeng Biotechnol
December 2024
Department of Rehabilitation Medicine, University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
Introduction: Parkinson's disease (PD) is characterized by muscle stiffness, bradykinesia, and balance disorders, significantly impairing the quality of life for affected patients. While motion pose estimation and gait analysis can aid in early diagnosis and timely intervention, clinical practice currently lacks objective and accurate tools for gait analysis.
Methods: This study proposes a multi-level 3D pose estimation framework for PD patients, integrating monocular video with Transformer and Graph Convolutional Network (GCN) techniques.
An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system.
Sci Rep
January 2025
Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.
The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. In order to improve load factor and efficiency, load-shifting techniques are frequently used in conjunction with additional complex constraints such as PHEV scheduling and battery life assessment. Pollutant reduction, however, is rarely highlighted as a primary goal.
View Article and Find Full Text PDFHighly Crystalline Contorted Coronene Homologous Molecule as Superior Organic Anode Material for Full-Cell Li-Ion Batteries.
ACS Nano
January 2025
Department of Energy Engineering, School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.
Organic anode materials have garnered attention for use in rechargeable Li-ion batteries (LIBs) owing to their lightweight, cost-effectiveness, and tunable properties. However, challenges such as high electrolyte solubility and limited conductivity, restrict their use in full-cell LIBs. Here, we report the use of highly crystalline Cl-substituted contorted hexabenzocoronene (Cl-cHBC) as an efficient organic anode for full-cell LIBs.
View Article and Find Full Text PDFDevelopment and Clinical Evaluation of a Contrast Optimizer for Contrast-Enhanced CT Imaging of the Liver.
J Comput Assist Tomogr
November 2024
From the Carl E. Ravin Advanced Imaging Labs, Center for Virtual Imaging Trials, Department of Radiology.
Objective: Patient characteristics, iodine injection, and scanning parameters can impact the quality and consistency of contrast enhancement of hepatic parenchyma in CT imaging. Improving the consistency and adequacy of contrast enhancement can enhance diagnostic accuracy and reduce clinical practice variability, with added positive implications for safety and cost-effectiveness in the use of contrast medium. We developed a clinical tool that uses patient attributes (height, weight, sex, age) to predict hepatic enhancement and suggest alternative injection/scanning parameters to optimize the procedure.
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