AIMC Topic: Cluster Analysis
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Exploratory cluster analysis of IL2Ra and associated biomarkers and complications after blunt chest trauma.
The journal of trauma and acute care surgery
Apr 14, 2025
BACKGROUND: Rib fractures compromise approximately 40% of all fractures in the United States. Despite their prevalence, the relationship between rib fractures, solid organ injuries, and immune responses remains poorly understood. This exploratory stu...
Children on wheels: Identifying crash determinants using cluster correspondence analysis.
Accident; analysis and prevention
Apr 10, 2025
Child bicyclists (14 years old and younger) are among the most vulnerable road users, facing significant risks of crashes that often result in severe injuries or fatalities. This study aims to identify key factors influencing child bicyclist crashes ...
scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data.
BMC genomics
Apr 7, 2025
BACKGROUND: Clustering scRNA-seq data plays a vital role in scRNA-seq data analysis and downstream analyses. Many computational methods have been proposed and achieved remarkable results. However, there are several limitations of these methods. First...
Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles.
Scientific reports
Apr 5, 2025
Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to its diverse clinical manifestations and underlying biological complexity. This study explored machine learning approaches to enhance ASD screening acc...
CCA: Contrastive cluster assignment for supervised and semi-supervised medical image segmentation.
Neural networks : the official journal of the International Neural Network Society
Mar 26, 2025
Transformers have shown great potential in vision tasks such as semantic segmentation. However, most of the existing transformer-based segmentation models neglect the cross-attention between pixel features and class features which impedes the applica...
Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.
PloS one
Mar 25, 2025
BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that has significant impacts on patients' quality of life and poses a substantial economic burden on society.
Uncovering hidden subtypes in dementia: An unsupervised machine learning approach to dementia diagnosis and personalization of care.
Journal of biomedical informatics
Mar 19, 2025
OBJECTIVE: Dementia represents a growing public health challenge, affecting an increasing number of individuals. It encompasses a broad spectrum of cognitive impairments, ranging from mild to severe stages, each of which demands varying levels of car...
Compressed Representation of Extreme Learning Machine with Self-Diffusion Graph Denoising Applied for Dissecting Molecular Heterogeneity.
Journal of computational biology : a journal of computational molecular cell biology
Mar 19, 2025
Molecular heterogeneity exists in many biological systems, such as major malignancies or diverse cell populations. Clustering of gene expression profiles has been widely used to dissect molecular heterogeneity. One drawback common to most clustering ...
Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data.
Journal of chemical information and modeling
Mar 19, 2025
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemic...
Kinetic Pattern Recognition in Home-Based Knee Rehabilitation Using Machine Learning Clustering Methods on the Slider Digital Physiotherapy Device: Prospective Observational Study.
JMIR formative research
Mar 18, 2025
BACKGROUND: Recent advancements in rehabilitation sciences have progressively used computational techniques to improve diagnostic and treatment approaches. However, the analysis of high-dimensional, time-dependent data continues to pose a significant...
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