Fig. 3
From: Small sample-based disease diagnosis model acquisition in medical human-centered computing
Auxiliary diagnosis model acquisition process. The specific workflow of the method includes four steps: collecting medical image data sets from the hospital; in the small sample method, inputting the seed data set into the designed variational auto-encoder to generate the image, and in the zero sample method, using ZASL to generate medical image data set; using the extended data set from the previous step to train deep neural network to obtain medical auxiliary diagnosis model; and using the trained medical auxiliary diagnosis model to test the test set to evaluate the model performance