Johnson & Johnson Surgical Vision, Inc.

Jeroen Van Der Donckt

Guang-ming Dai

Benjamin Straker

Gilles Vandewiele

Michael Rademaker

Joshua Young

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.

Growing community of inventors

Oudenaarde, Belgium

Jeroen Van Der Donckt