Identifying new subgroups among children and adolescents with obesity and metabolic syndrome requires advanced clustering techniques capable of analyzing complex multidimensional data. This study aimed to employ machine learning methods to enhance th...
Selecting appropriate machine learning (ML) methods for domain-specific tasks remains a persistent challenge, particularly in medicine where datasets are often small, heterogeneous, and incomplete. Traditional benchmarking strategies rely on limited ...
Identification of virulence factors (VFs) is critical for expanding our knowledge on bacterial pathogenesis and also for developing targeted strategies for the prevention and treatment of related infectious diseases. Understanding virulence factors r...
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides extensive opportunities to explore cellular heterogeneity but is often limited by substantial technical noise and variability. The prevalence of zero counts, arising from both biological var...
Biomedical physics & engineering express
Nov 19, 2025
Artificial intelligence (AI) systems are increasingly used in medical imaging for disease diagnosis, yet their vulnerability to adversarial attacks poses significant risks for clinical deployment. In this work, we systematically evaluate the suscepti...
Positron imaging has shown great potential in industrial non-destructive testing due to its high sensitivity and ability to reveal internal structures of complex components. However, reconstructing high-quality images from positron emission data rema...
To improve the accuracy and efficiency of crack segmentation in ancient wooden structures, we propose a lightweight deep neural network architecture, termed SMG-Net. The core innovation of this model lies in its multi-cooperative perception mechanism...
Journal of chemical information and modeling
Nov 18, 2025
We present a simple methodology that allows the building and sharing of predictive models without compromising the confidentiality of the structures of the training series. Multiple shared models can be used to obtain ensemble models, providing bette...
Accurate cell type classification is critical for downstream analysis in single-cell RNA sequencing (scRNA-seq). Most existing methods rely on a single type of feature representation-such as statistical, information theory, matrix factorization, or d...
Liver cancer has a high incidence and mortality rate globally, particularly in patients requiring intensive care unit (ICU) admission. Early prediction of in-hospital mortality for these patients is crucial, yet lacking reliable tools. This study aim...
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