AIMC Topic: Keratoconus

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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...

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).

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...

Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks.

PloS one
Purpose Prediction of the ectasia screening index, an estimator provided by the Casia2 instrument for identifying keratoconus, from raw optical coherence tomography data using convolutional neural networks. Methods Three convolutional neural networks...

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...

Artificial Doctors: Performance of Chatbots as a Tool for Patient Education on Keratoconus.

Eye & contact lens
PURPOSE: We aimed to compare the answers given by ChatGPT, Bard, and Copilot and that obtained from the American Academy of Ophthalmology (AAO) website to patient-written questions related to keratoconus in terms of accuracy, understandability, actio...