Results 261 to 270 of about 621,417 (312)
Objective We developed a novel electronic health record sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Retracted: CNN-Based Cross-Modal Residual Network for Image Synthesis. [PDF]
International BR.
europepmc +1 more source
Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie +3 more
wiley +1 more source
Synthetic Genitourinary Image Synthesis via Generative Adversarial Networks: Enhancing Artificial Intelligence Diagnostic Precision. [PDF]
Van Booven DJ +8 more
europepmc +1 more source
Objective Systemic lupus erythematosus (SLE) is a heterogenous inflammatory condition with widely varying global prevalence estimates. The frequency of SLE in the general population of Australia has been reported to be notably lower than contemporary estimates in countries such as the United States or United Kingdom, at 19 to 39 per 100,000 as opposed ...
Lucinda Roper +7 more
wiley +1 more source
A Foggy Weather Simulation Algorithm for Traffic Image Synthesis Based on Monocular Depth Estimation. [PDF]
Tang M, Zhao Z, Qiu J.
europepmc +1 more source
Image synthesis of apparel stitching defects using deep convolutional generative adversarial networks. [PDF]
Ul-Huda N +5 more
europepmc +1 more source
VSG-GAN: A high-fidelity image synthesis method with semantic manipulation in retinal fundus image. [PDF]
Liu J +6 more
europepmc +1 more source
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Unsupervised text-to-image synthesis
Pattern Recognition, 2021Abstract Recently, text-to-image synthesis has achieved great progresses with the advancement of the Generative Adversarial Network (GAN). However, training the GAN models requires a large amount of pairwise image-text data, which is extremely labor-intensive to collect.
Jiebo Luo
exaly +2 more sources

