Embodiments include controlling a processor to access an image of a region of tissue demonstrating cancerous pathology; segment a cellular nucleus represented in the image; extract a first set of features from the segmented cellular nucleus; classify the segmented nucleus as a lymphocyte or non-lymphocyte based on the first set of features; for a segmented nucleus classified as a lymphocyte: computing a set of contextual features; assign the segmented nucleus classified as a lymphocyte to one of a plurality of clusters based on the set of contextual features; compute a frequency distribution of the clustered segmented nuclei classified as lymphocytes; provide the frequency distribution to a machine learning classifier; receive, from the machine learning classifier, a classification of the region of tissue as likely to experience recurrence or unlikely to experience recurrence, based, at least in part, on the frequency distribution; and display the classification.