Method of training model for identification of disease, electronic device using method, and non-transitory storage medium

Abstract

A method training an AI model in disease identification establishes a disease identifying model, the model includes a convolutional neural network and a pyramid attention network. The pyramid attention network receives output of the convolutional neural network. The method obtains feature map sample set, the sample set being classified into training sets and verification sets. The method inputs each training set into the disease identifying model to train the model and outputs values of degree of confidence in correct identification of diseases. The method further verifies the trained models according to the verification sets. An electronic device and a non-transitory storage medium are also disclosed.