Alcon had 16 patents in artificial intelligence during Q2 2024. Alcon Inc filed patents in Q2 2024 for systems and methods related to determining compatibility of multi-focal contact lenses for presbyopia correction, assessing vision quality using machine learning models, visualization systems for ophthalmic procedures, performing ophthalmic surgical procedures by integrating pre-operative and intra-operative data, and enhancing ophthalmic visualization by combining images from different parts of the electromagnetic spectrum. GlobalData’s report on Alcon gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Alcon had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for using machine learning to predict contact lens compatibility (Patent ID: US20240197167A1)
The patent filed by Alcon Inc. describes systems and methods for determining the compatibility between a multi-focal contact lens and a patient seeking presbyopia vision correction. The system involves receiving a request from an eye-care professional (ECP) for selecting a contact lens for a consumer, obtaining a performance metric associated with the ECP, using a machine learning model to determine a customized compatibility index based on the performance metric, and presenting a report indicating the compatibility index. The system also includes features such as generating compatibility scores based on biometric information, adjusting compatibility score ranges based on ECP performance metrics, and predicting vision quality for the consumer using the contact lens.
The method outlined in the patent involves receiving a request from an ECP for determining compatibility between a particular lens and a patient, comparing performance information of different ECPs, selecting a compatibility index customized for the ECP based on patient attributes, and presenting a report indicating the compatibility index. Additional features of the method include providing a vision simulation to the patient, obtaining biometric data during the simulation, considering patient attributes like age and eye dryness index, and using vision quality data to train the machine learning model. The non-transitory machine-readable medium described in the patent stores instructions for performing operations related to selecting a contact lens, obtaining performance metrics, generating compatibility scores, and adjusting compatibility score ranges based on ECP performance metrics, among other functions.
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