Systems and methods for predicting patient outcome to cancer therapy

A method of predicting patient response to therapy, comprising:

• receiving a plurality of patient tissue image slides;
• receiving a plurality of patient outcome data;
• dividing the image slides into patches;
• receiving a plurality of labels correlated with a disease or lack thereof, wherein each label comprises of a morphological type;
• converting each patch to a patch vector;
• training an artificial intelligence network, based on the plurality of labels to identify the morphological types associated with each label in the image slides;
• generating labeled patch vectors, wherein the label of a patch vector is assigned based, at least partly, on the plurality of the labels and the morphological type expressed in the patch;
• clustering the labeled patch vectors, with an unsupervised artificial intelligence network, wherein each cluster corresponds to a morphological subtype expressed in the patch corresponding to the labeled patch vector and a patient outcome;
• generating a patch-level score for each patch based at least partly on the cluster to which the patch vector of the patch belongs;
• and
• generating a patient-level score for each patient, at least partly based on the patch-level scores generated for each patient.