Method and apparatus for supporting prediction of neurodevelopmental disorder using fundus image

Abstract

Provided are apparatuses, a non-transitory computer-readable medium or media, for predicting of neurodevelopmental disorder using a fundus image of a subject. In certain aspects, disclosed a method including the steps of: receiving the fundus image; processing the fundus image to classify one or more features contained in the fundus image using a machine learning model; and predicting, based on a classification, whether the fundus image is indicative of presence of neurodevelopmental disorder in the subject, wherein the machine learning model has been trained on stored fundus images obtained from at least two group of subjects who have previously been diagnosed as having the neurodevelopmental disorder, the machine learning model is trained by processes comprising; extracting a first embedding vector and a second embedding vector from a first fundus image and a second fundus image, respectively; and maximizing a similarity between the first embedding vector and the second embedding vector.