Machine learning for detection of diseases from external anterior eye images

Abstract

The present disclosure is directed to systems and methods that leverage machine learning for detection of eye or non-eye (e.g., systemic) diseases from external anterior eye images. In particular, a computing system can include and use one or more machine-learned disease detection models to provide disease predictions for a patient based on external anterior eye images of the patient. Specifically, in some example implementations, a computing system can obtain one or more external images that depict an anterior portion of an eye of a patient. The computing system can process the one or more external images with the one or more machine-learned disease detection models to generate a disease prediction for the patient relative to one or more diseases, including, as examples, diseases which present manifestations in a posterior of the eye (e.g., diabetic retinopathy) or systemic diseases (e.g., poorly controlled diabetes).