Ophthalmology

Glaucoma

Latest AI and machine learning research in glaucoma for healthcare professionals.

5,142 articles
Stay Ahead - Weekly Glaucoma research updates
Subscribe
Browse Specialties
Showing 85-105 of 5,142 articles
Altered dynamic large-scale brain networks and combined machine learning in primary angle-closure glaucoma.

Primary angle-closure glaucoma (PACG) is a severe and irreversible blinding eye disease characterize...

An automatic glaucoma grading method based on attention mechanism and EfficientNet-B3 network.

Glaucoma infection is rapidly spreading globally and the number of glaucoma patients is expected to ...

Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal...

The role of saliency maps in enhancing ophthalmologists' trust in artificial intelligence models.

PURPOSE: Saliency maps (SM) allow clinicians to better understand the opaque decision-making process...

Developing a privacy-preserving deep learning model for glaucoma detection: a multicentre study with federated learning.

BACKGROUND: Deep learning (DL) is promising to detect glaucoma. However, patients' privacy and data ...

Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review.

In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particula...

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.

Fairness (also known as equity interchangeably) in machine learning is important for societal well-b...

Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects.

BACKGROUND/AIMS: To assess the performance of deep-learning (DL) models for prediction of conversion...

Evaluation of machine learning approach for surgical results of Ahmed valve implantation in patients with glaucoma.

BACKGROUND: Ahmed valve implantation demonstrated an increasing proportion in glaucoma surgery, but ...

Artificial intelligence in retinal screening using OCT images: A review of the last decade (2013-2023).

BACKGROUND AND OBJECTIVES: Optical coherence tomography (OCT) has ushered in a transformative era in...

Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.

Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of ret...

Progression or Aging? A Deep Learning Approach for Distinguishing Glaucoma Progression From Age-Related Changes in OCT Scans.

PURPOSE: To develop deep learning (DL) algorithm to detect glaucoma progression using optical cohere...

A hybrid framework for glaucoma detection through federated machine learning and deep learning models.

BACKGROUND: Glaucoma, the second leading cause of global blindness, demands timely detection due to ...

Breaking Barriers in Behavioral Change: The Potential of Artificial Intelligence-Driven Motivational Interviewing.

Patient outcomes in ophthalmology are greatly influenced by adherence and patient participation, whi...

Advancements and turning point of artificial intelligence in ophthalmology: A comprehensive analysis of research trends and collaborative networks.

Artificial intelligence (AI) has emerged as a transformative force with great potential in various f...

Artificial intelligence based glaucoma and diabetic retinopathy detection using MATLAB - retrained AlexNet convolutional neural network.

BACKGROUND: Glaucoma and diabetic retinopathy (DR) are the leading causes of irreversible retinal da...

Remote and low-cost intraocular pressure monitoring by deep learning of speckle patterns.

SIGNIFICANCE: Glaucoma, a leading cause of global blindness, disproportionately affects low-income r...

Novel Technologies in Artificial Intelligence and Telemedicine for Glaucoma Screening.

PURPOSE: To provide an overview of novel technologies in telemedicine and artificial intelligence (A...

Explainable artificial intelligence in the design of selective carbonic anhydrase I-II inhibitors via molecular fingerprinting.

Inhibiting the enzymes carbonic anhydrase I (CA I) and carbonic anhydrase II (CA II) presents a pote...

Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data.

OBJECTIVE: To develop machine learning (ML) models, using pre and intraoperative surgical parameters...

Browse Specialties