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Classification Criteria For Pars Planitis.

American journal of ophthalmology
PURPOSE: To determine classification criteria for pars planitis.

Classification Criteria for Spondyloarthritis/HLA-B27-Associated Anterior Uveitis.

American journal of ophthalmology
PURPOSE: The purpose of this study was to determine classification criteria for spondyloarthritis/HLA-B27-associated anterior uveitis DESIGN: Machine learning of cases with spondyloarthritis/HLA-B27-associated anterior uveitis and 8 other anterior uv...

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Nature biomedical engineering
Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneu...

FixationNet: Forecasting Eye Fixations in Task-Oriented Virtual Environments.

IEEE transactions on visualization and computer graphics
Human visual attention in immersive virtual reality (VR) is key for many important applications, such as content design, gaze-contingent rendering, or gaze-based interaction. However, prior works typically focused on free-viewing conditions that have...

Adaptive Weighting of Handcrafted Feature Losses for Facial Expression Recognition.

IEEE transactions on cybernetics
Due to the importance of facial expressions in human-machine interaction, a number of handcrafted features and deep neural networks have been developed for facial expression recognition. While a few studies have shown the similarity between the handc...

Diagnostic performance of artificial intelligence model for pneumonia from chest radiography.

PloS one
OBJECTIVE: The chest X-ray (CXR) is the most readily available and common imaging modality for the assessment of pneumonia. However, detecting pneumonia from chest radiography is a challenging task, even for experienced radiologists. An artificial in...

Uncertainty measurement of radiomics features against inherent quantum noise in computed tomography imaging.

European radiology
OBJECTIVES: Quantum noise is a random process in X-ray-based imaging systems. We addressed and measured the uncertainty of radiomics features against this quantum noise in computed tomography (CT) images.