AI Medical Compendium Topic

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

Glaucoma

Showing 141 to 150 of 309 articles

Clear Filters

Machine Learning Techniques for Ophthalmic Data Processing: A Review.

IEEE journal of biomedical and health informatics
Machine learning and especially deep learning techniques are dominating medical image and data analysis. This article reviews machine learning approaches proposed for diagnosing ophthalmic diseases during the last four years. Three diseases are addre...

Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

IEEE journal of biomedical and health informatics
The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-a...

Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma can prevent irreversible vision loss and glaucomatous structural damage...

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

Translational vision science & technology
PURPOSE: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression.

Deep learning in glaucoma with optical coherence tomography: a review.

Eye (London, England)
Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has made significant breakthroughs in medical imaging, particularly for image classification and pattern recognition. In ophthalmology, applying DL for glauco...

Deep-learning-based enhanced optic-disc photography.

PloS one
Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient cooperation, small pupils, or media opacities can limit the performance of ODP. The purpose of this ...

Detection of Glaucoma Deterioration in the Macular Region with Optical Coherence Tomography: Challenges and Solutions.

American journal of ophthalmology
PURPOSE: Macular imaging with optical coherence tomography (OCT) measures the most critical retinal ganglion cells (RGCs) in the human eye. The goal of this perspective is to review the challenges to detection of glaucoma progression with macular OCT...

[Artificial intelligence for eye care].

Nederlands tijdschrift voor geneeskunde
Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already been applied in ophthalmic diabetes care. AI-systems currently detect diabetic retinopathy in gener...

Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop a deep learning system for automated glaucomatous optic neuropathy (GON) detection using ultra-widefield fundus (UWF) images.

An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma.

Translational vision science & technology
PURPOSE: The purpose of this study was to classify the spatial patterns of retinal nerve fiber layer thickness (RNFLT) and assess their associations with visual field (VF) loss in glaucoma.