Ghent, Belgium

Gilles Vandewiele

USPTO Granted Patents = 1 

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Gilles Vandewiele: Innovator in Machine Learning for IOL Power Prediction

Introduction

Gilles Vandewiele is a prominent inventor based in Ghent, Belgium. He has made significant contributions to the field of ophthalmology through his innovative work in machine learning applications for intraocular lens (IOL) power prediction. His expertise and dedication to improving surgical outcomes have positioned him as a key figure in the industry.

Latest Patents

Gilles Vandewiele holds a patent for the "Prediction of IOL power." This patent describes 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. The goal is to provide an individualized, highly accurate post-operative manifest refraction prediction. The determination engine generates a predictive feature set of one or more predictors associated with diagnostic measurements of one or more eyes. It performs a recursive selection operation using combinations within the predictive feature set and models to produce a most predictive subset, which has the highest prediction accuracy for post-operative manifest refraction.

Career Highlights

Gilles Vandewiele is currently associated with Johnson & Johnson Surgical Vision, Inc., where he continues to develop innovative solutions in the field of vision correction. His work has been instrumental in advancing the understanding and application of machine learning in ophthalmic surgery.

Collaborations

One of his notable collaborators is Guang-ming Dai, with whom he has worked on various projects aimed at enhancing surgical precision and patient outcomes.

Conclusion

Gilles Vandewiele's contributions to the field of ophthalmology through his innovative patent on IOL power prediction exemplify the impact of machine learning in medical technology. His work continues to pave the way for advancements in personalized patient care.

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