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.

Date of Patent:
Jun. 24, 2025

Filed:

May. 25, 2021
Applicant:

Alcon Inc., Fribourg, CH;

Inventors:

John Alfred Campin, Southlake, TX (US);

Brant Gillen, Southlake, TX (US);

Martin Gründig, Rangsdorf, DE;

Robert Moore, Tannay, CH;

George Hunter Pettit, Fort Worth, TX (US);

Mark Andrew Zielke, Lake Forest, CA (US);

Assignee:

ALCON INC., Fribourg, CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 3/10 (2006.01); A61B 3/00 (2006.01); A61B 3/103 (2006.01); G06N 3/08 (2023.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); A61B 34/10 (2016.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
A61B 3/10 (2013.01); A61B 3/0025 (2013.01); A61B 3/103 (2013.01); G06N 3/08 (2013.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); A61B 2034/108 (2016.02); G16H 50/20 (2018.01); G16H 50/30 (2018.01);
Abstract

A system and method for selecting an intraocular lens, for implantation into an eye, includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute a machine learning model trained with a training dataset. Execution of the instructions by the processor causes the controller to obtain pre-operative objective data for the patient, including one or more anatomic eye measurements. The controller is configured to obtain pre-operative questionnaire data for the patient, including at least one personality trait. The pre-operative objective data and the pre-operative questionnaire data are entered as respective inputs to the machine learning model. A predicted subjective outcome score for the patient is generated as an output of the machine learning model. The intraocular lens is selected based in part on the predicted subjective outcome score.


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