Method to improve instance selection in bootstrapping framework for concept extraction from text documents

A system for training a text report identification machine learning model and an image identification machine learning model, comprising:

• a memory;
• and
• a processor connected to the memory, the processor configured to:
• label a first set of unlabeled text reports based on matching concept phrases of a seed dictionary with concepts in the unlabeled text reports;
• input images associated with the first set of labeled text reports into an auto-encoder to obtain an encoded first set of images;
• calculate a set of first correlation matrices as a dot product of the first encoded images with their associated text report features;
• determine a distance between the set of first correlation matrices and a filter bank value associated with the auto-encoder;
• identify a first set of validated images as the images in the first set of images that have a distance less than a threshold value;
• and
• train the text report machine learning model using the labeled text reports associated with the set of first validated images.