Abstract: One or more methods of predicting expression levels. At least one of the methods includes preprocessing image data representing at least one biological image of a patient to generate preprocessed image data representing at least one preprocessed biological image of the patient; and applying a trained machine learning model to the preprocessed image data to predict, based at least partially on the at least one preprocessed biological image, an expression level of a biological indicator.

Abstract: Embodiments of the present disclosure include systems, methods, and non-transitory computer-readable storage media for automated determination of a patient tumor-immune phenotype from immunofluorescence (IF) image analysis of pathology slides based on a tumor infiltrating lymphocytes score, a non-tumor infiltrating lymphocytes score, and a non-tumor infiltrating lymphocytes at tumor margin score.