Latest AI and machine learning research in glaucoma for healthcare professionals.
This paper proposes an architecture of the system that provides support for collaborative research f...
OBJECTIVE: To clinically validate a convolutional neural network (CNN)-based Android smartphone app ...
The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering...
PURPOSE: Develop and test a deep learning (DL) algorithm for detecting referable glaucoma.
PurposeTo evaluate the appropriateness and readability of the responses generated by ChatGPT-4 and B...
BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical eval...
Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition ...
Glaucoma is characterised by progressive vision loss due to retinal ganglion cell deterioration, lea...
Glaucoma is a major cause of irreversible blindness, with primary open-angle glaucoma (POAG) being ...
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed ...
Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we...
Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR)...
The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. ...
OBJECTIVE: Code-free deep learning (CFDL) allows clinicians with no coding experience to build their...
BACKGROUND: While expert optometrists tend to rely on a deep understanding of the disease and intuit...
Glaucoma is an irreversible, progressive, degenerative eye disorder arising because of increased int...
Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, curr...
Fundus imaging, a technique for recording retinal structural components and anomalies, is essential ...
OBJECTIVE: For studies using real-world data, accurately identifying patients with phenotypes of int...
This paper systematically evaluates saliency methods as explainability tools for convolutional neura...
This study provides a bibliometric and bibliographic review of emerging applications of micro- and n...