Alcon had one patents in big data during Q2 2024. Alcon Inc has developed a system and method for assessing the vision quality of an eye using machine learning models. The controller receives wavefront aberration data, expresses it as Zernike polynomials, and obtains input factors for analysis. The machine learning model then generates vision correction factors based on the input factors. 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 big data as a theme in Q2 2024.
Recent Patents
Application: Vision quality assessment based on machine learning model and wavefront analysis (Patent ID: US20240188819A1)
The patent filed by Alcon Inc. describes a system and method for assessing the vision quality of an eye using machine learning models. The system includes a controller with a processor and memory that receives wavefront aberration data of the eye and expresses it as Zernike polynomials. These polynomials are used to generate input factors that are fed into machine learning models to analyze and generate vision correction factors, such as manifest refraction spherical equivalent values.
The system further includes multiple machine learning models, each trained on specific patient datasets with different eye dimensions. The training process involves receiving wavefront aberration measurements and manifest refraction spherical equivalent values, generating weight values for the models, and incorporating various wavefront coefficients for defocus, spherical aberration, and astigmatism. The vision correction factors produced can be manifest refraction spherical equivalent factors or log MAR uncorrected visual acuity factors. The machine learning models utilized in the system include neural networks and support vector regression models, and can handle both pre-operative and post-operative data for accurate assessment of vision quality.
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