Accurate intraocular lens (IOL) power calculation is critical in cataract surgery, especially in patients with extreme axial myopia where traditional formulas often yield inaccurate results. This study retrospectively evaluated the accuracy of two AI...
PURPOSE: To assess the accuracy of artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas compared with traditional methods in highly myopic eyes, and to evaluate their performance across varying axial lengths and cornea...
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, par...
PurposeTo quantify the decentration of the crystalline lens in a large Austrian adult cataractous and non-cataractous cohort and to predict decentration using biometric parameters.SettingKepler University Clinic, Linz, Austria.DesignRetrospective sin...
BACKGROUND: The purpose of the study was to evaluate the relationship between prediction errors (PEs) and ocular biometric variables in cataract surgery using nine intraocular lens (IOL) formulas with an explainable machine learning model.
OBJECTIVES: To analyse the accuracy of artificial intelligence (AI)-driven intraocular (IOL) calculation formulae, together with established formulae using the heteroscedastic methodology and the Eyetemis Analysis Tool.
OBJECTIVE: This study aimed to develop and evaluate a deep learning-based model that could automatically measure anterior segment (AS) parameters on preoperative ultrasound biomicroscopy (UBM) images of implantable Collamer lens (ICL) surgery candida...
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