Results 221 to 230 of about 85,194 (289)

Fast and standardized motor-hotspot determination with automated TMS mapping

open access: yes
Granö I   +16 more
europepmc   +1 more source

Association of HAMP Expression and CD8+ T‐Cell Infiltration With Atezolizumab–Bevacizumab Response in Hepatocellular Carcinoma

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
In hepatocellular carcinoma treated with atezolizumab–bevacizumab, responders showed RNA‐seq enrichment of immune and chemokine pathways with higher HAMP expression. In resected specimens, immunohistochemistry confirmed increased intratumoral CD8+ T‐cell density and hepcidin (HAMP), supporting HAMP plus CD8 as components of a composite predictor of ...
Shun Nakamura   +9 more
wiley   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

open access: yesAdvanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin   +4 more
wiley   +1 more source

Genetic regulation of sperm DNA methylation in cattle through meQTL mapping. [PDF]

open access: yesBMC Genomics
Fouéré C   +18 more
europepmc   +1 more source

Autonomous Recognition of Retained Secretions in Central‐Airway Based on Deep Learning for Adult Patients Receiving Invasive Mechanical Ventilation

open access: yesAdvanced Intelligent Systems, EarlyView.
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang   +6 more
wiley   +1 more source

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