  We show how to use random field theory in a supervised, energy-based model
for multiple pseudo image classification of 2D integer matrices. In the model,
each row of a 2D integer matrix is a pseudo image where a local receptive field
focuses on multiple portions of individual rows for simultaneous learning. The
model is used for a classification task consisting of presence of patient
biomarkers indicative of a particular disease.
