Machine learning techniques for predicting future visual acuity

Abstract

The methods and systems disclosed herein generally relate to systems and methods for predicting future visual acuity of a subject by using a machine learning model. An image of at least a portion of a retina of a subject may be processed by one or more first machine learning models to detect a set of retina-related segments. A segment-specific metric that characterizes a retinal-related segment of the set of retinal-related segments may be generated. The segment-specific metrics may be processed by using a second machine learning model to generate results corresponding to predictions that correspond to future visual acuity of the subject.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS [0002] This application claims the benefit of the filing date of European Patent Application No. 19205315.5, filed on October 25, 2019, the disclosure of which is hereby incorporated by reference in its entirety and for all purposes. technical field [0003] The methods and systems disclosed herein relate generally to systems and methods for predicting a subject's future visual acuity by using a segmentation processing machine learning model and a metric processing machine learning model. Background technique [0004] Eye-related disorders can cause severe vision loss in individuals. For example, macular degeneration is one of the leading causes of severe, irreversible vision loss that occurs when the macular region of the retina deteriorates. Often, the early stages of some eye-related diseases are asymptomatic and do not cause vision loss. However, in later stages, vision loss can occur suddenly and unexpectedly due to eye...

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In another example, DE FAUW J et al.: "Clinically applicable deep learning for diagnosis and referral in retinal disease", Nature Medicine, vol. 24, no. 9, August 13, 2018 (2018-08-13), p. Pages 1342-1350 disclose the use of classification networks to predict the severity of a subject's sight-threatening retinal disease, but not the subject's future visual acuity

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