The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 01, 2025
Filed:
Feb. 04, 2020
Smith & Nephew, Inc., Memphis, TN (US);
Smith & Nephew Asia Pacific Pte. Limited, Singapore, SG;
Smith & Nephew Orthopaedics Ag, Zug, CH;
Shawn P. Mcguan, San Clemente, CA (US);
Scott Kennedy Laster, Memphis, TN (US);
Zachary C. Wilkinson, Germantown, TN (US);
Sied W. Janna, Memphis, TN (US);
Daniel Farley, Memphis, TN (US);
SMITH & NEPHEW, INC., Memphis, TN (US);
SMITH & NEPHEW ORTHOPAEDICS AG, Zug, CH;
SMITH & NEPHEW ASIA PACIFIC PTE. LIMITED, Singapore, SG;
Abstract
Methods, non-transitory computer readable media, and surgical computing devices are illustrated that improve surgical planning using machine learning. With this technology, a machine learning model is trained based on historical case log data sets associated with patients that have undergone a surgical procedure. The machine learning model is applied to current patient data for a current patient to generate a predictor equation. The current patient data comprises anatomy data for an anatomy of the current patient. The predictor equation is optimized to generate a size, position, and orientation of an implant, and resections required to achieve the position and orientation of the implant with respect to the anatomy of the current patient, as part of a surgical plan for the current patient. The machine learning model is updated based on the current patient data and current outcome.