Prediction of IOL power

US12419511B2 · kind B2 · utility

Assignee

• Johnson & Johnson Surgical Vision, Inc. · US

Inventors

• Charles Scales · Greenville, US
• Guang-ming Dai · Fremont, US
• Joshua Young · Toronto, CA
• Jeroen Van Der Donckt · Oudenaarde, BE
• Michael Rademaker · Wondelgem, BE
• Benjamin Straker · Jacksonville, US
• Gilles Vandewiele · Wondelgem, BE

Key dates

• Filing date: Nov 7, 2022
• Grant date: Sep 23, 2025
• Expiry date: Feb 9, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/20
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Described are implementations of systems and methods for an improved machine learning-based system that incorporates pre-operative and intraoperative measurements captured during surgery, as well as additional patient-specific data, to provide an individualized, highly accurate post-operative manifest refraction prediction. According to some embodiments, a determination engine generates a predictive feature set of one or more predictors associated with diagnostic measurements of one or more eyes and performs a recursive selection operation using one or more combinations within the predictive feature set and one or more models to produce a most predictive subset, the most predictive subset having a highest prediction accuracy among other predictive subsets for post-operative manifest refraction. The determination engine generates a determination model by refining and retraining the one or more models of the recursive selection operation utilizing the most predictive subset.