1. An apparatus for automated selection of features of cells useful for classifying cell phenotype, said features extracted from one or more images of the cells, the apparatus comprising: (a) a memory for storing a code defining a set of instructions; and (b) a processor for executing the set of instructions, wherein the code comprises an automated feature selection module to identify a set S 2 of N 2 calculated features for classification of cell phenotype, wherein the automated image feature selection module is configured to: (i) determine a signal-to-noise ratio for each of a plurality of pairs of features from an original set S 0 of N 0 calculated features of cells in one or more images, wherein the signal-to-noise ratio of a given pair of features reflects an ability to use that pair of features to classify cell phenotype, and identify a predetermined number N p of feature pairs from the original set S 0 of N 0 calculated features, said N p pairs having the highest signal-to-noise ratio, wherein N p is an integer ≧2; and (ii) identify the set S 2 of N 2 calculated features for classification of cell phenotype from among the members of the N p pairs of calculated features.