AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Glaucoma

Showing 91 to 100 of 309 articles

Clear Filters

Deep Learning-Based Noise Reduction Improves Optical Coherence Tomography Angiography Imaging of Radial Peripapillary Capillaries in Advanced Glaucoma.

Current eye research
PURPOSE: We applied deep learning-based noise reduction (NR) to optical coherence tomography-angiography (OCTA) images of the radial peripapillary capillaries (RPCs) in eyes with glaucoma and investigated the usefulness of this method as an objective...

Deep learning approaches based improved light weight U-Net with attention module for optic disc segmentation.

Physical and engineering sciences in medicine
Glaucoma is a major cause of blindness worldwide, and its early detection is essential for the timely management of the condition. Glaucoma-induced anomalies of the optic nerve head may cause variation in the Optic Disc (OD) size. Therefore, robust O...

A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design.

Ophthalmology. Glaucoma
PURPOSE: To investigate the efficacy of a deep learning regression method to predict macula ganglion cell-inner plexiform layer (GCIPL) and optic nerve head (ONH) retinal nerve fiber layer (RNFL) thickness for use in glaucoma neuroprotection clinical...

Automated diagnosing primary open-angle glaucoma from fundus image by simulating human's grading with deep learning.

Scientific reports
Primary open-angle glaucoma (POAG) is a leading cause of irreversible blindness worldwide. Although deep learning methods have been proposed to diagnose POAG, it remains challenging to develop a robust and explainable algorithm to automatically facil...

Multi-task deep learning for glaucoma detection from color fundus images.

Scientific reports
Glaucoma is an eye condition that leads to loss of vision and blindness if not diagnosed in time. Diagnosis requires human experts to estimate in a limited time subtle changes in the shape of the optic disc from retinal fundus images. Deep learning m...

An annotated corpus of clinical trial publications supporting schema-based relational information extraction.

Journal of biomedical semantics
BACKGROUND: The evidence-based medicine paradigm requires the ability to aggregate and compare outcomes of interventions across different trials. This can be facilitated and partially automatized by information extraction systems. In order to support...

Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings.

Scientific reports
Several artificial intelligence algorithms have been proposed to help diagnose glaucoma by analyzing the functional and/or structural changes in the eye. These algorithms require carefully curated datasets with access to ocular images. In the current...

Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

Scientific reports
In this study, we aimed to facilitate the current diagnostic assessment of glaucoma by analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) feature from optical coherence tomography (OCT) images. The data (n = 100 ...

Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.

Eye (London, England)
OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-DCNN) to jointly segment the optic disc (OD) and optic cup (OC) in retinal fundus images for precise cup-to-disc ratio (CDR) measurement and glaucoma ...

Diagnostic Accuracy of Artificial Intelligence in Glaucoma Screening and Clinical Practice.

Journal of glaucoma
PURPOSE: Artificial intelligence (AI) has been shown as a diagnostic tool for glaucoma detection through imaging modalities. However, these tools are yet to be deployed into clinical practice. This meta-analysis determined overall AI performance for ...