AI Medical Compendium Topic

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Visual Fields

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Deep learning visual field global index prediction with optical coherence tomography parameters in glaucoma patients.

Scientific reports
The aim of this study was to predict three visual filed (VF) global indexes, mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI), from optical coherence tomography (OCT) parameters including Bruch's Membrane Opening-Mi...

Artificial intelligence for glaucoma: state of the art and future perspectives.

Current opinion in ophthalmology
PURPOSE OF REVIEW: To address the current role of artificial intelligence (AI) in the field of glaucoma.

Predicting glaucoma progression using deep learning framework guided by generative algorithm.

Scientific reports
Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomog...

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

Translational vision science & technology
PURPOSE: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).

Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability.

Ophthalmology. Glaucoma
PURPOSE: Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and study the impact of using this DLM on sample size requirements for neuroprotective trials.

Prediction and Detection of Glaucomatous Visual Field Progression Using Deep Learning on Macular Optical Coherence Tomography.

Journal of glaucoma
PRCIS: A deep learning model trained on macular OCT imaging studies detected clinically significant functional glaucoma progression and was also able to predict future progression.

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

American journal of ophthalmology
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...

A multi-label transformer-based deep learning approach to predict focal visual field progression.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression...