Abstract: Provided are apparatuses, a non-transitory computer-readable medium or media, and methods for supporting predicting of vascular disease using a fundus image of a subject. In certain aspects, disclosed a method including the steps of: extracting a feature information from a first fundus image of the subject based on a machine learning model; generating a second fundus image having a feature which is corresponding to the feature information by mapping a saliency factor to the first fundus image; and displaying the first fundus image and the second fundus image on a display device.

Abstract: Provided are apparatuses, a non-transitory computer-readable medium or media, and methods for supporting reading of a fundus image of a subject. In certain aspects, disclosed a method including the steps of: extracting a first feature information from a first fundus image of the subject based on a machine learning model; generating a second fundus image having a second feature information by mapping an adversarial factor to the first fundus image so that the first feature information is changed; and displaying the first fundus image having the first feature information and the second fundus image having the second feature information on a display device.

Abstract: Provided are apparatuses, a non-transitory computer-readable medium or media, and methods for supporting predicting of vascular disease using a fundus image of a subject. In certain aspects, disclosed a method including the steps of: extracting a feature information from a first fundus image of the subject based on a machine learning model; generating a second fundus image having a feature which is corresponding to the feature information by mapping a saliency factor to the first fundus image; and displaying the first fundus image and the second fundus image on a display device.

Abstract: Provided are apparatuses, a non-transitory computer-readable medium or media, and methods for supporting reading of a fundus image of a subject. In certain aspects, disclosed a method including the steps of: extracting a first feature information from a first fundus image of the subject based on a machine learning model; generating a second fundus image having a second feature information by mapping an adversarial factor to the first fundus image so that the first feature information is changed; and displaying the first fundus image having the first feature information and the second fundus image having the second feature information on a display device.

Abstract: Disclosed are a method of manufacturing a reduced graphene oxide pattern which includes forming a graphene oxide pattern on a substrate and providing the graphene oxide pattern with a white light pulse to reduce the graphene oxide, a reduced graphene oxide obtained by the method, and an electronic device and a thin film transistor including the reduced graphene oxide.