AIMC Topic: Cluster Analysis

Clear Filters Showing 11 to 20 of 1361 articles

Understanding Dermatologists' Acceptance of Digital Health Interventions: Cross-Sectional Survey and Cluster Analysis.

JMIR human factors May 21, 2025
BACKGROUND: Digital health interventions (DHIs) have the potential to enhance dermatological care by improving quality, patient empowerment, and efficiency. However, adoption remains limited, particularly in Germany.
Dermatologists Telemedicine Germany Surveys and Questionnaires Attitude of Health Personnel Cluster Analysis Digital Health Female Adult Cross-Sectional Studies Male Middle Aged Humans
View on PubMed DOI

[Cluster predictors of trajectories of leisure-time physical activity intensity in men and women from ELSA-Brasil].

Cadernos de saude publica May 19, 2025
The maintenance of physical activity over time is a challenge for public health. Predictors of different physical activity intensities have not been sufficiently analyzed. This study aimed to identify clusters of trajectories of physical activity int...
Humans Female Brazil Exercise Surveys and Questionnaires Adult Male Middle Aged Cluster Analysis Sex Factors Leisure Activities Socioeconomic Factors Longitudinal Studies
View on PubMed DOI

ADEPT: An advanced data exploration and processing tool for clinical data insights.

Computer methods and programs in biomedicine May 17, 2025
BACKGROUND AND OBJECTIVE: The rapid growth of clinical data creates challenges in analysis and interpretation for medical professionals. To address these issues, we developed the Advanced Data Exploration and Processing Tool (ADEPT), integrating data...
Data Mining Support Vector Machine Cluster Analysis Area Under Curve Humans Machine Learning Software Algorithms Logistic Models
View on PubMed DOI

Learning to solve combinatorial optimization problems with heterophily.

Neural networks : the official journal of the International Neural Network Society May 7, 2025
Graph Neural Networks (GNNs) are widely used to address combinatorial optimization problems. However, many popular GNNs struggle to generalize to heterophilic scenarios where adjacent nodes tend to be with different labels or dissimilar features, suc...
Cluster Analysis Neural Networks, Computer Machine Learning Algorithms Humans
View on PubMed DOI

Analyzing and predicting global happiness index via integrated multilayer clustering and machine learning models.

PloS one Apr 30, 2025
This study addresses the research objective of predicting global happiness and identifying its key drivers. We propose a novel predictive framework that integrates unsupervised and supervised machine learning techniques to uncover the complex pattern...
Cluster Analysis Humans Happiness Machine Learning Social Support
View on PubMed DOI

GINClus: RNA structural motif clustering using graph isomorphism network.

NAR genomics and bioinformatics Apr 26, 2025
Ribonucleic acid (RNA) structural motif identification is a crucial step for understanding RNA structure and functionality. Due to the complexity and variations of RNA 3D structures, identifying RNA structural motifs is challenging and time-consuming...
Cluster Analysis Software Algorithms RNA Nucleic Acid Conformation Deep Learning Nucleotide Motifs
View on PubMed DOI

Identification of Risk Group for Root Caries and Analysis of Associated Factors in Older Adults Using Unsupervised Machine Learning Clustering.

Clinical interventions in aging Apr 24, 2025
PURPOSE: This study aimed to identify the high-risk group for root caries using unsupervised machine learning and to explore the associated factors.
Cluster Analysis Female Unsupervised Machine Learning ROC Curve Root Caries Cross-Sectional Studies Humans Risk Factors Logistic Models Male Aged Age Factors Risk Assessment
View on PubMed DOI

LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data.

Proceedings of the National Academy of Sciences of the United States of America Apr 23, 2025
Disease and behavior subtype identification is of significant interest in biomedical research. However, in many settings, subtype discovery is limited by a lack of robust statistical clustering methods appropriate for binary data. Here, we introduce ...
Principal Component Analysis Cardiovascular Diseases Latent Class Analysis Cluster Analysis Humans Machine Learning Algorithms
View on PubMed DOI

Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

Scientific reports Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Radiomics Male Middle Aged Angiogenesis Inhibitors Treatment Outcome Cluster Analysis Retrospective Studies Female Aged Humans Diabetic Retinopathy Tomography, Optical Coherence Unsupervised Machine Learning Macular Edema Visual Acuity Vascular Endothelial Growth Factor A Principal Component Analysis
View on PubMed DOI

BL-FlowSOM: Consistent and Highly Accelerated FlowSOM Based on Parallelized Batch Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Apr 17, 2025
The recent increase in the dimensionality of cytometry data has led to the development of various computational analysis methods. FlowSOM is one of the best-performing clustering methods but has room for improvement in terms of the consistency and sp...
Principal Component Analysis Flow Cytometry Humans Machine Learning Software Algorithms Computational Biology Cluster Analysis
View on PubMed DOI
Popular Topics
Recent Journals