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Keratoconus

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Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
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...

Multidisease Deep Learning Neural Network for the Diagnosis of Corneal Diseases.

American journal of ophthalmology
PURPOSE: To report a multidisease deep learning diagnostic network (MDDN) of common corneal diseases: dry eye syndrome (DES), Fuchs endothelial dystrophy (FED), and keratoconus (KCN) using anterior segment optical coherence tomography (AS-OCT) images...

Artificial Intelligence Efficiently Identifies Regional Differences in the Progression of Tomographic Parameters of Keratoconic Corneas.

Journal of refractive surgery (Thorofare, N.J. : 1995)
PURPOSE: To develop an artificial intelligence (AI) model to effectively assess local versus global progression of keratoconus using multiple tomographic parameters.

[Deep learning based lesion detection from anterior segment optical coherence tomography images and its application in the diagnosis of keratoconus].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
To developed an image analysis system of anterior segment optical coherence tomography (AS-OCT) examination results based on deep learning technology, and to evaluate its effect in identifying various types of corneal pathologies and quantified indi...

Artificial intelligence applications in different imaging modalities for corneal topography.

Survey of ophthalmology
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 ...

A deep learning approach for successful big-bubble formation prediction in deep anterior lamellar keratoplasty.

Scientific reports
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...

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
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 Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps.

Translational vision science & technology
PURPOSE: To develop and assess the accuracy of a hybrid deep learning construct for detecting keratoconus (KCN) based on corneal topographic maps.

Protocol for the diagnosis of keratoconus using convolutional neural networks.

PloS one
Keratoconus is the corneal disease with the highest reported incidence of 1:2000. The treatment's level of success highly depends on how early it was started. Subsequently, a fast and highly capable diagnostic tool is crucial. While there are many co...

Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Sensors (Basel, Switzerland)
Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-edge technology is limited with reference to the global population. A significant way to improve overa...