Classification of cell states and lines by machine learning algorithms based on holographic data

We report the development and validation of machine learning classification algorithms aimed at determination of cell lines and states. Three types of classifiers were used to analyze cellular parameters obtained by digital holographic microscopy. The highest classification accuracy was achieved with the support vector machine learning algorithm. The classification accuracy over 90% was demonstrated for classifications between three cell lines and three cell states of the same line.