AIMC Topic: Arthritis, Rheumatoid
Clear Filters Showing 51 to 60 of 117 articles
Using Unsupervised Machine Learning Methods to Cluster Comorbidities in a Population-Based Cohort of Patients With Rheumatoid Arthritis.
Arthritis care & research
Sep 15, 2022
OBJECTIVE: To identify clusters of comorbidities in patients with rheumatoid arthritis (RA) using 4 methods and to compare to patients without RA.
Recent advances in the use of machine learning and artificial intelligence to improve diagnosis, predict flares, and enrich clinical trials in lupus.
Current opinion in rheumatology
Aug 24, 2022
PURPOSE OF REVIEW: Machine learning is a computational tool that is increasingly used for the analysis of medical data and has provided the promise of more personalized care.
Automated evaluation of rheumatoid arthritis from hand radiographs using Machine Learning and deep learning techniques.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Jul 12, 2022
The aim and objectives of the study are as follows: (i) to implement automated patch-based classification of hand X-ray images using modified pre-trained convolutional neural network (CNN) models; (ii) to develop a customized CNN model for automated ...
Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning.
Disease markers
Feb 9, 2022
OBJECTIVES: Synovial fibroblasts (SFs) play an important role in the development and progression of rheumatoid arthritis (RA). However, the pathogenic mechanism of SFs remains unclear. The objective of this study was to investigate how neuropeptides ...
A deep learning classification of metacarpophalangeal joints synovial proliferation in rheumatoid arthritis by ultrasound images.
Journal of clinical ultrasound : JCU
Jan 17, 2022
OBJECTIVE: To evaluate if an automatic classification of rheumatoid arthritis (RA) metacarpophalangeal joint conditions in ultrasound images is feasible by deep learning (DL) method, to provide a more objective, automated, and fast way of RA diagnosi...
Automated Classification of Rheumatoid Arthritis, Osteoarthritis, and Normal Hand Radiographs with Deep Learning Methods.
Journal of digital imaging
Jan 11, 2022
Rheumatoid arthritis and hand osteoarthritis are two different arthritis that causes pain, function limitation, and permanent joint damage in the hands. Plain hand radiographs are the most commonly used imaging methods for the diagnosis, differential...
Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.
Rheumatology international
Jan 11, 2022
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitu...
A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images.
Computers in biology and medicine
Dec 23, 2021
OBJECTIVE: Rheumatoid arthritis (RA) is a chronic disease characterized by erosive symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease. Cartilage damage is one of the most relevant determinants of physical disabil...
Association of TLR 9 gene polymorphisms with remission in patients with rheumatoid arthritis receiving TNF-α inhibitors and development of machine learning models.
Scientific reports
Oct 11, 2021
Toll-like receptor (TLR)-4 and TLR9 are known to play important roles in the immune system, and several studies have shown their association with the development of rheumatoid arthritis (RA) and regulation of tumor necrosis factor alpha (TNF-α). Howe...
DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.
Nature communications
Oct 6, 2021
Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31137
- Neural Networks, Computer 29769
- Algorithms 26908
- Deep Learning 26418
- Artificial Intelligence 24354
- Robotics 13322
- Image Processing, Computer-Assisted 9552
- Retrospective Studies 9136
- Magnetic Resonance Imaging 6198
- Reproducibility of Results 5602
- Tomography, X-Ray Computed 4778
- Support Vector Machine 4695
- Computational Biology 4246
- Brain 4056
- Computer Simulation 3887
Recent Journals
- Scientific reports 6082
- Sensors (Basel, Switzerland) 4794
- PloS one 4044
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1868
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1137
- Journal of chemical information and modeling 1006
- Nature communications 959
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 862
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 829