AIMC Topic: Keratoconus

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Deep Learning Models Used in the Diagnostic Workup of Keratoconus: A Systematic Review and Exploratory Meta-Analysis.

Cornea Feb 1, 2024
PURPOSE: The prevalence of keratoconus in the general population is reported to be up to 1 of 84. Over the past 2 decades, diagnosis and management evolved rapidly, but keratoconus screening in clinical practice is still challenging and asks for impr...
Deep Learning Keratoconus Corneal Topography Humans Algorithms
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Computer-aided diagnosis of keratoconus through VAE-augmented images using deep learning.

Scientific reports Nov 23, 2023
Detecting clinical keratoconus (KCN) poses a challenging and time-consuming task. During the diagnostic process, ophthalmologists are required to review demographic and clinical ophthalmic examinations in order to make an accurate diagnosis. This stu...
Humans Computers Neural Networks, Computer Retrospective Studies Deep Learning Keratoconus
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Artificial intelligence for detecting keratoconus.

The Cochrane database of systematic reviews Nov 15, 2023
BACKGROUND: Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on clinical examination and corneal imaging; though in the early stages, ...
Case-Control Studies Keratoconus Physical Examination Artificial Intelligence Cross-Sectional Studies Humans
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Novel deep learning approach to estimate rigid gas permeable contact lens base curve for keratoconus fitting.

Contact lens & anterior eye : the journal of the British Contact Lens Association Sep 28, 2023
INTRODUCTION: Rigid gas permeable contact lenses (RGP) are the most efficient means of providing optimal vision in keratoconus. RGP fitting can be challenging and time-consuming for ophthalmologists and patients. Deep learning predictive models could...
Deep Learning Keratoconus Corneal Topography Humans Retrospective Studies Contact Lenses Prosthesis Fitting
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Comparison of different corneal imaging modalities using artificial intelligence for diagnosis of keratoconus: a systematic review and meta-analysis.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Jul 7, 2023
PURPOSE: This review was designed to compare different corneal imaging modalities using artificial intelligence (AI) for the diagnosis of keratoconus (KCN), subclinical KCN (SKCN), and forme fruste KCN (FFKCN).
Cornea Keratoconus Corneal Topography Artificial Intelligence Reproducibility of Results Humans
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KeratoScreen: Early Keratoconus Classification With Zernike Polynomial Using Deep Learning.

Cornea Apr 20, 2022
PURPOSE: We aimed to investigate the usefulness of Zernike coefficients (ZCs) for distinguishing subclinical keratoconus (KC) from normal corneas and to evaluate the goodness of detection of the entire corneal topography and tomography characteristic...
Adolescent ROC Curve Corneal Topography Keratoconus Cornea Deep Learning Adult Sensitivity and Specificity Humans Retrospective Studies Young Adult Algorithms
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Protocol for the diagnosis of keratoconus using convolutional neural networks.

PloS one Feb 18, 2022
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...
Sensitivity and Specificity Diagnosis, Computer-Assisted Keratoconus Humans Neural Networks, Computer
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Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Sensors (Basel, Switzerland) Feb 4, 2022
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...
Humans Artificial Intelligence Keratoconus Child Smartphone Machine Learning Health Services Accessibility Adolescent
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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...
Decision Trees Keratoconus Bayes Theorem Logistic Models Support Vector Machine Databases, Factual Early Diagnosis Severity of Illness Index Computer Simulation Linear Models Computational Biology Humans Cornea Neural Networks, Computer Machine Learning Algorithms
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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 ...
Humans Deep Learning Neural Networks, Computer Keratoconus Cornea
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