We developed an unsupervised machine learning algorithm and applied it to big corneal parameters to identify and monitor keratoconus stages. A big dataset of corneal swept source optical coherence tomography (OCT) images of 12,242 eyes acquired from ...
BACKGROUND AND OBJECTIVE: Accurate staging of keratoconus (KC) is crucial for timely intervention and improving patient quality of life. Unlike prior studies that relied on traditional base machine learning (ML) models, this paper proposes a more adv...
CLINICAL RELEVANCE: Artificial intelligence has undergone a rapid evolution and large language models (LLMs) have become promising tools for healthcare, with the ability of providing human-like responses to questions. The capabilities of these tools ...
In certain ocular conditions, such as in eyes with keratoconus or after corneal laser surgery, Higher Order Aberrations (HOAs) may be dramatically elevated. Accurately recording interpretable wavefronts in such highly aberrated eyes using Shack-Hartm...
Translational vision science & technology
May 1, 2025
PURPOSE: To identify and analyze clinical risk factors and imaging parameters influencing the outcomes of deep anterior lamellar keratoplasty (DALK) for advanced keratoconus (KC) using an artificial intelligence (AI) model.
Translational vision science & technology
Dec 2, 2024
PURPOSE: Eye rubbing is considered to play a significant role in the progression of keratoconus and of corneal ectasia following refractive surgery. To our knowledge, no tool performs an objective quantitative evaluation of eye rubbing using a device...
Journal of cataract and refractive surgery
Dec 1, 2024
PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.
Translational vision science & technology
May 1, 2024
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...
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