AI Medical Compendium Topic

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Corneal Topography

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A Deep Learning-Based Framework for Accurate Evaluation of Corneal Treatment Zone After Orthokeratology.

Translational vision science & technology
PURPOSE: Given the robust effectiveness of inhibiting myopia progression, orthokeratology has gained increasing popularity worldwide. However, identifying the boundary and the center of reshaped corneal area (i.e., treatment zone) is the main challen...

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.

KeratoScreen: Early Keratoconus Classification With Zernike Polynomial Using Deep Learning.

Cornea
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...

New simulation software to predict postoperative corneal stiffness before laser vision correction.

Journal of cataract and refractive surgery
PURPOSE: To develop a new virtual surgery simulation platform to predict postoperative corneal stiffness (Kc mean ) after laser vision correction (LVC) surgery.

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
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).

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
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 Based Prediction of Myopia Control Effect in Children Treated With Overnight Orthokeratology.

Eye & contact lens
OBJECTIVES: To develop and validate a deep learning-based model for predicting 12-month axial length (AL) elongation using baseline factors and early corneal topographic changes in children treated with orthokeratology (Ortho-K) and to investigate th...

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

Cornea
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...

Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Translational vision science & technology
PURPOSE: Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit...

Development and evaluation of a deep neural network model for orthokeratology lens fitting.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
PURPOSE: To optimise the precision and efficacy of orthokeratology, this investigation evaluated a deep neural network (DNN) model for lens fitting. The objective was to refine the standardisation of fitting procedures and curtail subjective evaluati...