Results 131 to 140 of about 2,131,360 (300)

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Algorithms and complexity of range clustering

open access: yesNetworks, 2018
We introduce a novel criterion in clustering that seeks clusters with limited range of values associated with each cluster's elements. In clustering or classification the objective is to partition a set of objects into subsets, called clusters or classes, consisting of similar objects so that different clusters are as dissimilar as possible. We propose
openaire   +4 more sources

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein   +7 more
wiley   +1 more source

Real‐World Safety and Effectiveness of JAK Inhibitors in Systemic Sclerosis: A Propensity‐Matched Study From the EUSTAR Cohort

open access: yesArthritis Care &Research, EarlyView.
Objective JAK inhibitors (JAKi) have shown promising effects in early‐phase studies of systemic sclerosis (SSc). We aimed to assess the safety and explore the effectiveness of JAKi compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the European Scleroderma Trials and Research Group (EUSTAR) cohort was ...
Stefano Di Donato   +27 more
wiley   +1 more source

Fuzzy clustering of univariate and multivariate time series by genetic multiobjective optimization [PDF]

open access: yes
Given a set of time series, it is of interest to discover subsets that share similar properties. For instance, this may be useful for identifying and estimating a single model that may fit conveniently several time series, instead of performing the usual
S. Bandyopadhyay, R. Baragona, U. Maulik
core  

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

open access: yesArthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil   +7 more
wiley   +1 more source

Coping with new Challenges in Clustering and Biomedical Imaging [PDF]

open access: yes, 2011
The last years have seen a tremendous increase of data acquisition in different scientific fields such as molecular biology, bioinformatics or biomedicine.
Oswald, Annahita
core   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

open access: yesArthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling   +4 more
wiley   +1 more source

Selecting Clustering Algorithms for Identity-By-Descent Mapping. [PDF]

open access: yesPac Symp Biocomput, 2023
Shemirani R   +7 more
europepmc   +1 more source

Clustering on Spatial Data Sets Using Extended Linked Clustering Algorithms [PDF]

open access: yes, 2018
Various clustering algorithms (CA) have been reported in literature, to group data into clusters in diverse domains. Literature further reported that, these CAs work satisfactorily either on pure numerical data or on pure categorical data and perform ...
K Lakshmaiah
core  

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