AIMC Topic: Keratoconus
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A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps.
Translational vision science & technology
Dec 1, 2021
PURPOSE: To develop and assess the accuracy of a hybrid deep learning construct for detecting keratoconus (KCN) based on corneal topographic maps.
[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
Jun 11, 2021
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...
Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.
JAMA ophthalmology
May 1, 2020
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...
[Assistant diagnose for subclinical keratoconus by artificial intelligence].
[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Dec 11, 2019
To investigate the diagnosis of normal cornea, subclinical keratoconus and keratoconus by artifical intelligence. Diagnostic study. From January 2016 to January 2019, who admitted to Tianjin Eye Hospital from 18 to 48 years old, with an average of ...
[Application of Deep Learning in Early Diagnosis Assistant System of Keratoconus].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Mar 30, 2019
In view of the problem that there is no standard diagnosis for early stage keratoconus disease,at the same time to assist the special examiner and ophthalmologist to make the early diagnosis effectively,the advantages and disadvantages of each testin...
Biomechanics of the Healthy and Keratoconic Corneas: A Combination of the Clinical Data, Finite Element Analysis, and Artificial Neural Network.
Current pharmaceutical design
Jan 1, 2018
BACKGROUND: Keratoconus is recognized by asymmetrical thinning and bulging of the cornea, resulting in distortion in the surface of the cornea. Keratoconus also alters the biomechanical properties of the cornea, which can be an indicator of the healt...
Evaluation of a Machine-Learning Classifier for Keratoconus Detection Based on Scheimpflug Tomography.
Cornea
Jun 1, 2016
PURPOSE: To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with othe...
Accuracy of machine learning classifiers using bilateral data from a Scheimpflug camera for identifying eyes with preclinical signs of keratoconus.
Journal of cataract and refractive surgery
Feb 1, 2016
PURPOSE: To describe the topographic and tomographic characteristics of normal fellow eyes of unilateral keratoconus cases and to evaluate the accuracy of machine learning classifiers in discriminating healthy corneas from the normal fellow corneas.
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