AIMC Topic: Corneal Topography

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Dual vision transformer with bio-inspired optimization for explainable keratoconus classification.

International ophthalmology
BACKGROUND: Keratoconus (KCN) is a progressive degenerative corneal disorder characterized by corneal thinning and cone-shaped protrusion, leading to significant visual impairment if not detected early. Accurate staging of KCN using corneal topograph...

Artificial intelligence for predicting the axial length response of orthokeratology in myopic children.

Physics in medicine and biology
This study aimed to automate the extraction of local corneal topography (CT) features in myopic children undergoing orthokeratology (OK), evaluate their causal effects on axial length (AL) control, and develop a predictive model for AL progression.We...

Exploring biomarkers for keratoconus: current insights and future directions.

Molecular biology reports
Keratoconus (KC) is a progressive corneal disorder characterized by thinning of the cornea and conical protrusion leading to distorted vision and blindness. The disease often marks in adolescence and progresses until the mid-40s, with varying degrees...

The application of artificial intelligence-based algorithms in predicting the progression of keratoconus: a systematic review.

International ophthalmology
PURPOSE: To conduct a systematic review of studies examining the use of artificial intelligence (AI) algorithms in predicting the progression of keratoconus (KCN).

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Metaheuristic-optimized swin transformer with SHAP explainability for keratoconus classification from corneal topography maps.

International ophthalmology
Keratoconus (KCN) is an uncommon corneal disorder where the central cornea undergoes advanced thinning and causes non-uniform astigmatism. This results in metamorphopsia and potential vision loss if it is left untreated. Early detection of KCN is maj...

An optimized multi-scale dilated attention layer for keratoconus disease classification.

International ophthalmology
INTRODUCTION: Keratoconus (KCN) is a progressive and non-inflammatory corneal disorder characterized by thinning and conical deformation of the cornea, resulting in visual impairment. Early and accurate detection is crucial to prevent disease progres...

Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data.

Scientific reports
Keratoconus is a progressive eye disease characterized by the thinning and bulging of the cornea, leading to visual impairment. Early and accurate diagnosis is crucial for effective management and treatment. This study investigates the application of...

Advances in machine learning for keratoconus diagnosis.

International ophthalmology
PURPOSE: To review studies reporting the role of Machine Learning (ML) techniques in the diagnosis of keratoconus (KC) over the past decade, shedding light on recent developments while also highlighting the existing gaps between academic research and...