AIMC Topic: Cornea
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Change patterns in the corneal sub-basal nerve and corneal aberrations in patients with dry eye disease: An artificial intelligence analysis.
Experimental eye research
Dec 10, 2021
We aimed to investigate the change patterns in corneal sub-basal nerve morphology and corneal intrinsic aberrations in dry eye disease (DED). Our study included 229 eyes of 155 patients with DED and 40 eyes of 20 healthy control. We used the Oculus k...
Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.
Computational and mathematical methods in medicine
Nov 16, 2021
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...
Diagnostic armamentarium of infectious keratitis: A comprehensive review.
The ocular surface
Nov 13, 2021
Infectious keratitis (IK) represents the leading cause of corneal blindness worldwide, particularly in developing countries. A good outcome of IK is contingent upon timely and accurate diagnosis followed by appropriate interventions. Currently, IK is...
Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Nov 2, 2021
BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surf...
Fully automated grading system for the evaluation of punctate epithelial erosions using deep neural networks.
The British journal of ophthalmology
Oct 20, 2021
PURPOSE: The goal was to develop a fully automated grading system for the evaluation of punctate epithelial erosions (PEEs) using deep neural networks.
KerNet: A Novel Deep Learning Approach for Keratoconus and Sub-Clinical Keratoconus Detection Based on Raw Data of the Pentacam HR System.
IEEE journal of biomedical and health informatics
Oct 6, 2021
Keratoconus is one of the most severe corneal diseases, which is difficult to detect at the early stage (i.e., sub-clinical keratoconus) and possibly results in vision loss. In this paper, we propose a novel end-to-end deep learning approach, called ...
A deep learning approach for successful big-bubble formation prediction in deep anterior lamellar keratoplasty.
Scientific reports
Sep 17, 2021
The efficacy of deep learning in predicting successful big-bubble (SBB) formation during deep anterior lamellar keratoplasty (DALK) was evaluated. Medical records of patients undergoing DALK at the University of Cologne, Germany between March 2013 an...
Artificial intelligence applications in different imaging modalities for corneal topography.
Survey of ophthalmology
Aug 25, 2021
Interpretation of topographical maps used to detect corneal ectasias requires a high level of expertise. Several artificial intelligence (AI) technologies have attempted to interpret topographic maps. The purpose of this study is to provide a review ...
Preventing corneal blindness caused by keratitis using artificial intelligence.
Nature communications
Jun 18, 2021
Keratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of op...
A Novel Automatic Morphologic Analysis of Eyelids Based on Deep Learning Methods.
Current eye research
Jun 14, 2021
: To propose a deep-learning-based approach to automatically and objectively evaluate morphologic eyelid features using two-dimensional(2D) digital photographs and to assess the agreement between automatic and manual measurements.: The 2D photographs...
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