CPC A61B 5/0022 (2013.01) [A61B 5/4082 (2013.01); A61B 5/4088 (2013.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/171 (2022.01); G16H 30/40 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06V 10/32 (2022.01)] | 9 Claims |
1. A method for generating a classifier to classify facial images for cognitive disorder in humans, comprising:
receiving a labeled dataset including set of facial images, wherein each of the facial image is labeled depending on whether it represents a cognitive disorder condition;
extracting, from the each of the facial image in the set of facial images, at least one learning facial feature indicative of a cognitive disorder;
feeding the at least one extracted facial feature to produce a machine learning trained model, wherein the at least one extracted facial feature is identified to represent a human face; and
generating a classifier based on the machine learning trained model, wherein the classifier is generated and ready when the trained model includes enough facial features processed by a machine learning model, wherein the classifier is configured to map a detection facial feature from a detection facial image to a score and output a plurality of scores indicating a stage of a cognitive decline.
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