Automated disease detection using retinal images

A system, comprising:

• memory;
• a processor;
• and
• computer-executable instructions stored in the memory and executable by the processor to perform operations comprising:
• receiving an image of a retina of an eye of a patient;
• receiving, from an electronic medical record (EMR) of the patient, patient data corresponding to the patient;
• determining a feature in the image;
• determining, by inputting the feature and at least a portion of the patient data as input to a machine learning (ML) model, a confidence level associated with a first disease;
• determining, based on the confidence level being higher than a threshold, a recommendation for screening of the patient based on the first disease;
• and
• providing, to the EMR of the patient, an output indicating the recommendation.

A non-transitory computer-readable storage medium storing processor-executable instructions that, when executed, cause one or more processors to:

• receive, from an optical imaging device, an image of a retina of an eye of a patient;
• access, from an electronic medical record (EMR) storage, EMR data of the patient;
• determine a feature in the image;
• determine, by inputting the feature and at least a portion of the EMR data as input to a machine learning (ML) model, a confidence level associated with a first disease;
• and
• determine, based on the confidence level being higher than a threshold, a recommendation for screening of the patient based on the first disease.