Glaucoma

Utilizing human intelligence in artificial intelligence for detecting glaucomatous fundus images using human-in-the-loop machine learning.

PURPOSE: For diagnosing glaucomatous damage, we have employed a novel convolutional neural network (CNN) from TrueColor confocal fundus images to conquer the black box dilemma in artificial intelligence (AI). This neural network with CNN architecture with human-in-the-loop (HITL) data annotation helps not only in diagnosing glaucoma but also in predicting and locating detailed signs in the glaucom...

Predicting Glaucoma Progression Requiring Surgery Using Clinical Free-Text Notes and Transfer Learning With Transformers.

PURPOSE: We evaluated the use of massive transformer-based language models to predict glaucoma progression requiring surgery using ophthalmology clinical notes from electronic health records (EHRs).

Peripapillary Atrophy Segmentation and Classification Methodologies for Glaucoma Image Detection: A Review.

Information-based image processing and computer vision methods are utilized in several healthcare organizations to diagnose diseases. The irregulariti...

AxonDeep: Automated Optic Nerve Axon Segmentation in Mice With Deep Learning.

PURPOSE: Optic nerve damage is the principal feature of glaucoma and contributes to vision loss in many diseases. In animal models, nerve health has t...

Predicting 10-2 Visual Field From Optical Coherence Tomography in Glaucoma Using Deep Learning Corrected With 24-2/30-2 Visual Field.

PURPOSE: To investigate whether a correction based on a Humphrey field analyzer (HFA) 24-2/30-2 visual field (VF) can improve the prediction performan...

Updates in deep learning research in ophthalmology.

Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garn...

Identification of glaucoma from fundus images using deep learning techniques.

PURPOSE: Glaucoma is one of the preeminent causes of incurable visual disability and blindness across the world due to elevated intraocular pressure w...

Deep Learning-based Diagnosis of Glaucoma Using Wide-field Optical Coherence Tomography Images.

PURPOSE: (1) To evaluate the performance of deep learning (DL) classifier in detecting glaucoma, based on wide-field swept-source optical coherence to...

Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of gla...

Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest.

PURPOSE: To compare change over time in eye-specific optical coherence tomography (OCT) retinal nerve fiber layer (RNFL)-based region-of-interest (ROI...

An ensemble framework based on Deep CNNs architecture for glaucoma classification using fundus photography.

Glaucoma is a chronic ocular degenerative disease that can cause blindness if left untreated in its early stages. Deep Convolutional Neural Networks (...

Rapid classification of glaucomatous fundus images.

We propose a new method for training convolutional neural networks (CNNs) and use it to classify glaucoma from fundus images. This method integrates r...

Strategies to Improve Convolutional Neural Network Generalizability and Reference Standards for Glaucoma Detection From OCT Scans.

PURPOSE: To develop and evaluate methods to improve the generalizability of convolutional neural networks (CNNs) trained to detect glaucoma from optic...

Detection of glaucoma using retinal fundus images: A comprehensive review.

Content-based image analysis and computer vision techniques are used in various health-care systems to detect the diseases. The abnormalities in a hum...

Use of Telepresence Robots in Glaucoma Patient Education.

PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improv...

Artificial intelligence and complex statistical modeling in glaucoma diagnosis and management.

PURPOSE OF REVIEW: The field of artificial intelligence has grown exponentially in recent years with new technology, methods, and applications emergin...

Re: Phene et al.: Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs (Ophthalmology. 2019;126:1627-1639).

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a C...

The potential application of artificial intelligence for diagnosis and management of glaucoma in adults.

BACKGROUND: Glaucoma is the most frequent cause of irreversible blindness worldwide. There is no cure, but early detection and treatment can slow the ...

Artificial intelligence in cornea, refractive, and cataract surgery.

PURPOSE OF REVIEW: The subject of artificial intelligence has recently been responsible for the advancement of many industries including aspects of me...