AIMC Topic: Corneal Diseases
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Characterising corneal changes in aniridia-related keratopathy using in vivo confocal microscopy and a self-supervised AI model.
BMJ open ophthalmology
Jul 16, 2025
PURPOSE: To investigate whether corneal changes observed via in vivo confocal microscopy (IVCM) in patients with aniridia-related keratopathy (ARK) reflect clinical severity.
Detection of Ocular Surface Squamous Neoplasia Using Artificial Intelligence With Anterior Segment Optical Coherence Tomography.
American journal of ophthalmology
Feb 19, 2025
PURPOSE: To develop and validate a deep learning (DL) model to differentiate ocular surface squamous neoplasia (OSSN) from pterygium and pinguecula using high-resolution anterior segment optical coherence tomography (AS-OCT).
Humans
Artificial Intelligence
Retrospective Studies
Female
Middle Aged
Carcinoma, Squamous Cell
Tomography, Optical Coherence
Conjunctival Neoplasms
Deep Learning
Anterior Eye Segment
Aged, 80 and over
Diagnosis, Differential
Reproducibility of Results
Corneal Diseases
Adult
Aged
Pterygium
Sensitivity and Specificity
Male
The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading.
Scientific reports
Jan 9, 2025
We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims to investigate the influence of AI's misleading guidance on ophthalmologists' responses. This cross...
Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases.
The British journal of ophthalmology
Sep 20, 2024
AIM: To develop an artificial intelligence (AI) algorithm that diagnoses cataracts/corneal diseases from multiple conditions using smartphone images.
Artificial intelligence in corneal diseases: A narrative review.
Contact lens & anterior eye : the journal of the British Contact Lens Association
Aug 27, 2024
Corneal diseases represent a growing public health burden, especially in resource-limited settings lacking access to specialized eye care. Artificial intelligence (AI) offers promising solutions for automating the diagnosis and management of corneal ...
Interpretable Machine Learning-Based Risk Score for Predicting 10-Year Corneal Graft Survival After Penetrating Keratoplasty and Deep Anterior Lamellar Keratoplasty in Asian Eyes.
Cornea
Jul 24, 2024
PURPOSE: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score.
Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review.
Journal francais d'ophtalmologie
Jul 15, 2024
In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particularly in managing corneal diseases, a major reversible cause of blindness. This review explores AI's transformative role in the corneal subspecialty, wh...
Predicting Success in Descemet Membrane Endothelial Keratoplasty Using Machine Learning.
Cornea
Jun 20, 2024
PURPOSE: This study aimed to predict early graft failure (GF) in patients who underwent Descemet membrane endothelial keratoplasty based on donor characteristics.
Artificial Intelligence for Lamellar Keratoplasty.
Klinische Monatsblatter fur Augenheilkunde
Mar 19, 2024
The training of artificial intelligence (AI) is becoming increasingly popular. More and more studies on lamellar keratoplasty are also being published. In particular, the possibility of non-invasive and high-resolution imaging technology of optical c...
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