1. A computer-implemented method of whole tissue classification steps of: training a Multi-Layer Perceptron (MLP) classifier in a supervised manner wherein labels are given only at a tissue level, the training using a multiple-instance learning variant of backpropagation, wherein an input feature vector that generates the largest output value within all regions of interest (ROI) is back-propagated; training a tissue classifier with an output of the MLP classifier; for a given tissue image: segmenting the tissue image into ROIs; extracting a vector of features from each of the ROIs; applying the MLP classifier to the vector of features of each ROI thereby obtaining a set of probabilities; providing the probabilities to a tissue classifier; and outputting a diagnosis of the whole-tissue.