Machine learning for detection of diseases from external anterior eye images

A computer-implemented method for training a machine-learned disease detection model to provide disease predictions based on external anterior eye images, the method comprising:

• obtaining one or more external images that depict an anterior portion of an eye of a patient, wherein one or more ground truth disease labels are associated with the one or more external images;
• processing the one or more external images with one or more machine-learned disease detection models to generate a disease prediction for the patient relative to one or more diseases, wherein the one or more diseases comprise one or more disease manifestations in the eye, and wherein the one or more disease manifestations in the eye comprise one or more disease manifestations in a fundus of the eye;
• evaluating a loss function that compares the disease prediction for the patient with the one or more ground truth disease labels;
• and
• modifying one or more values of one or more parameters of the machine-learned disease detection models based at least in part on the loss function.

One or more non-transitory computer-readable media that collectively store:

• one or more machine-learned disease detection models configured to provide disease predictions based on external anterior eye images;
• and
• instructions that, when executed by one or more processors, cause a computing system to perform operations, the operations comprising:
• obtaining one or more external images that depict an anterior portion of an eye of a patient;
• processing 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,
• wherein the one or more diseases comprise one or more disease manifestations in the eye, and
• wherein the one or more disease manifestations in the eye comprise one or more disease manifestations in a fundus of the eye;
• and
• providing the disease prediction for the patient relative to the one or more diseases as an output.