AIMC Topic: Glaucoma
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Diagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.
JMIR medical informatics
Jan 29, 2025
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
Jan 28, 2025
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...
OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning.
Scientific reports
Jan 28, 2025
Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. T...
Optimising deep learning models for ophthalmological disorder classification.
Scientific reports
Jan 24, 2025
Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological diseases. Disorders such as hypertension, glaucoma, and diabetic retinopathy are indicated by structura...
Systematic application of saliency maps to explain the decisions of convolutional neural networks for glaucoma diagnosis based on disc and cup geometry.
Biomedical physics & engineering express
Jan 21, 2025
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...
Advancements and Prospects in Nanorobotic Applications for Ophthalmic Therapy.
ACS biomaterials science & engineering
Jan 17, 2025
This study provides a bibliometric and bibliographic review of emerging applications of micro- and nanotechnology in treating ocular diseases, with a primary focus on glaucoma. We aim to identify key research trends and analyze advancements in device...
Glaucoma detection and staging from visual field images using machine learning techniques.
PloS one
Jan 17, 2025
PURPOSE: In this study, we investigated the performance of deep learning (DL) models to differentiate between normal and glaucomatous visual fields (VFs) and classify glaucoma from early to the advanced stage to observe if the DL model can stage glau...
Machine Learning Approaches in High Myopia: Systematic Review and Meta-Analysis.
Journal of medical Internet research
Jan 3, 2025
BACKGROUND: In recent years, with the rapid development of machine learning (ML), it has gained widespread attention from researchers in clinical practice. ML models appear to demonstrate promising accuracy in the diagnosis of complex diseases, as we...
Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.
Chinese medical journal
Dec 23, 2024
BACKGROUND: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC deat...
Exploring transparency: A comparative analysis of explainable artificial intelligence techniques in retinography images to support the diagnosis of glaucoma.
Computers in biology and medicine
Dec 19, 2024
Machine learning models are widely applied across diverse fields, including nearly all segments of human activity. In healthcare, artificial intelligence techniques have revolutionized disease diagnosis, particularly in image classification. Although...
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