1000 Eyes Lens Biometry Study: Artificial Intelligence for Intraocular Lens Power Calculation

Overview

The main purpose of the study is to develop an AI approach to improve intraocular lens power calculations.

Cataract surgery is one of the most commonly performed surgeries worldwide and has a high postoperative patient satisfaction rate. Despite significant improvement in measurement methods and artificial lens power calculation formulas, miscalculations and subsequently refractive error still occur after cataract surgery. Most current artificial lens calculation methods use regression formulas. The concept of artificial intelligence (AI) has only recently found use and only in a rudimentary way. Examples include the Hill-RBF calculator and the Ladas superformula, but at least the "superformula" does not use a true AI approach and the results are no better than those obtained with conventional methods. The main purpose of the study is to develop an AI approach to improve intraocular lens power calculations. The data will be used for the following analysis: * To compare the new AI method with conventional and modern formula (main question) * To compare the refractive error for different eye lengths * To use a ray tracing method to quantify sources of error in patients with a refractive surprise of at least 1.0 diopter * To evaluate a novel concept of outlier testing using a modified nonparametric Walsh test This study will be multi-center and partially prospective. Data from 1000 patients who have already had cataract surgery will be analyzed. All patients will be invited for a visit to the recruitment clinic and the measurements will be performed.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Central Contacts