Results 161 to 170 of about 8,736,056 (314)
DEEP framework for deep learning
, 2020 The DEEP-Hybrid-DataCloud project developed a distributed architecture to leverage intensive computing techniques such as needed for deep learning. The DEEP framework applies a hybrid-cloud approach and provides a set of tools and cloud services to cover
Lloret, Lara +25 more
core
Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea +53 more
wiley +1 more source
Deep learning through sparse and low-rank modeling /
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better ...
Huang, Thomas S.editor. +2 more
core
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
, 2019 In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data.
Latyr Fall, Cheikh +9 more
core +1 more source
Arthritis 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
Deep learning for brain tumour segmentation
Deep Learning revolutionizes brain tumour segmentation in medical imaging, enabling automatic detection with high accuracy. A lot of software with emphasis on automatic classification and segmentation in the medical field was developed with Deep Learning
Beishenova, Saltanat
core
Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
Arthritis 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
Arthritis Care &Research, EarlyView.Biomedical research involving US veterans continues to advance health care beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both veteran ...
Austin M. Wheeler +20 more
wiley +1 more source