AIMC Topic: Glaucoma

Clear Filters Showing 21 to 30 of 330 articles

Application of machine learning techniques in GlaucomAI system for glaucoma diagnosis and collaborative research support.

Scientific reports
This paper proposes an architecture of the system that provides support for collaborative research focused on analysis of data acquired using Triggerfish contact lens sensor and devices for continuous monitoring of cardiovascular system properties. T...

The performance of ChatGPT-4 and Bing Chat in frequently asked questions about glaucoma.

European journal of ophthalmology
PurposeTo evaluate the appropriateness and readability of the responses generated by ChatGPT-4 and Bing Chat to frequently asked questions about glaucoma.MethodThirty-four questions were generated for this study. Each question was directed three time...

AI for glaucoma, Are we reporting well? a systematic literature review of DECIDE-AI checklist adherence.

Eye (London, England)
BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical evaluation of artificial intelligence (AI) decision support systems (DSS) reported in glaucoma care. Artificial Intelligence applications within glaucoma ...

Predicting visual field global and local parameters from OCT measurements using explainable machine learning.

Scientific reports
Glaucoma is characterised by progressive vision loss due to retinal ganglion cell deterioration, leading to gradual visual field (VF) impairment. The standard VF test may be impractical in some cases, where optical coherence tomography (OCT) can offe...

Mathematical Modeling and Artificial Intelligence to Explore Connections Between Glaucoma and the Gut Microbiome.

Medicina (Kaunas, Lithuania)
Glaucoma is a major cause of irreversible blindness, with primary open-angle glaucoma (POAG) being the most prevalent form. While elevated intraocular pressure (IOP) is a well-known risk factor for POAG, emerging evidence suggests that the human gut...

Using ChatGPT-4 in visual field test assessment.

Clinical & experimental optometry
CLINICAL RELEVANCE: Visual field testing is essential in the diagnosis and management of various ophthalmic diseases, particularly glaucoma. Integrating ChatGPT-4 into the interpretation of these tests has the potential to aid clinical decision makin...

Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports
Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we have collected information on 2572 subjects and used generalized linear model to investigate the association between urinary heavy metal levels and g...

Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images.

Computers in biology and medicine
Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR) and Rim-to-Disc Ratio (RDR). However, precise segmentation of the optic cup and disc is challenging due to low-contrast boundaries and the interferen...

Diagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.

JMIR medical informatics
BACKGROUND: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variati...

On QSPR analysis of glaucoma drugs using machine learning with XGBoost and regression models.

Computers in biology and medicine
Glaucoma is an irreversible, progressive, degenerative eye disorder arising because of increased intraocular pressure, resulting in eventual vision loss if untreated. The QSPR relates, mathematically, by employing various algorithms, a specified prop...