Results 91 to 100 of about 463,538 (280)

Structure-guided deep multi-view clustering

Information Fusion
Deep multi-view clustering seeks to utilize the abundant information from multiple views to improve clustering performance. However, most of the existing clustering methods often neglect to fully mine multi-view structural information and fail to explore the distribution of multi-view data, limiting clustering performance. To address these limitations,
Jinrong Cui, Xiaohuang Wu, Haitao Zhang, Chongjie Dong, Jie Wen   +4 more
openaire   +2 more sources

Validation of the Pediatric Arthritis Ultrasound Scoring System for the Elbow, Wrist, and Finger Joints in Children With Juvenile Idiopathic Arthritis

Arthritis Care &Research, EarlyView.
Objective We aimed to validate the Pediatric Arthritis Ultrasound Scoring System (PAUSS) for upper extremity joints in children with juvenile idiopathic arthritis (JIA). Methods Children with JIA were evaluated for elbow, wrist, or finger arthritis by clinical examination (CE) and musculoskeletal ultrasound (MSUS) with images scored according to the ...
Patricia Vega‐Fernandez, Pinar Ozge Avar‐Aydin, Kelly Rogers, Daniel J. Lovell, Jennifer Huggins, Alexei Grom, Hermine I. Brunner, Grant S. Schulert, Sheila T. Angeles‐Han, Mekibib Altaye, Amy Cassedy, Arthur B. Meyers, Tracy V. Ting   +12 more
wiley   +1 more source

Sparse Multi-View K-Means Clustering

IEEE Access
In machine learning, k-means clustering is an unsupervised leaning technique to partition the data into k clusters that are homogeneous within the cluster and heterogeneous between clusters.
Miin-Shen Yang, Shazia Parveen
doaj   +1 more source

Risk of Retinopathy Associated with Long‐Term Use of Hydroxychloroquine in Patients with Rheumatic Diseases: A Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among patients receiving long‐term HCQ with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain optical coherence tomography (SD‐OCT) for screening ...
Narsis Daftarian, Chloe Yue, Steve D Levasseur, Hui Xie, J. Antonio Avina‐Zubieta   +4 more
wiley   +1 more source

Balanced Multi-view Clustering

Multi-view clustering (MvC) aims to integrate information from different views to enhance the capability of the model in capturing the underlying data structures. The widely used joint training paradigm in MvC is potentially not fully leverage the multi-view information, since the imbalanced and under-optimized view-specific features caused by the ...
Li, Zhenglai, Wang, Jun, Tang, Chang, Zhu, Xinzhong, Zhang, Wei, Liu, Xinwang   +5 more
openaire   +2 more sources

Cumulative Social Disadvantage and Disease Activity in Juvenile Idiopathic Arthritis: A Childhood Arthritis and Rheumatology Research Alliance Registry Study

Arthritis Care &Research, Accepted Article.
Background Social determinants of health (SDOH) contribute to JIA disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship between cumulative social disadvantage, neighborhood disadvantage, and JIA ...
William Daniel Soulsby, John Boscardin, Andrea Knight, Daniel B. Horton, Karine Toupin‐April, Emily von Scheven, The CARRA Registry Investigators and for the CARRA Health Equity Work Group   +6 more
wiley   +1 more source

Integrative subspace clustering by common and specific decomposition for applications on cancer subtype identification

BMC Medical Genomics, 2019
Background Recent high throughput technologies have been applied for collecting heterogeneous biomedical omics datasets. Computational analysis of the multi-omics datasets could potentially reveal deep insights for a given disease.
Yin Guo, Huiran Li, Menglan Cai, Limin Li   +3 more
doaj   +1 more source

Multi-view Graph Clustering Algorithm Based on Dual Contrastive Learning and Hard Sample Mining [PDF]

Jisuanji gongcheng
As a key research direction in the field of graph mining, graph clustering aims to discover substructures or node groups with similarities from graph data and classify them into the same cluster.
QIAN Lifeng, LI Jing, ZOU Xuxi, CHEN Yu, GU Yalin, WEI Xunhu
doaj   +1 more source

Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach

, 2013
Computer vision tasks are traditionally defined and evaluated using semantic categories. However, it is known to the field that semantic classes do not necessarily correspond to a unique visual class (e.g. inside and outside of a car).
Azizpour, Hossein, Carlsson, Stefan
core  

Multi-Task Multi-View Clustering

IEEE Transactions on Knowledge and Data Engineering, 2016
Multi-task clustering and multi-view clustering have severally found wide applications and received much attention in recent years. Nevertheless, there are many clustering problems that involve both multi-task clustering and multi-view clustering, i.e., the tasks are closely related and each task can be analyzed from multiple views.
Xiaotong Zhang, Xianchao Zhang, Han Liu, Xinyue Liu   +3 more
openaire   +1 more source