Abstract: Techniques for performing diagnostic assessments based on digital pathology data are disclosed. In one particular embodiment, the techniques may be realized as a method for performing a diagnostic assessment based on digital pathology data comprising obtaining first digital pathology data comprising intensity information, the first digital pathology data being associated with a plurality of regions of interest in a biological sample; applying first machine learning models to the first digital pathology data, the first machine learning models identifying first regions of interest among the plurality of regions of interest based on the intensity information; applying second machine learning models to the first digital pathology data, the second machine learning models identifying at least one pattern associated with at least one of the first regions of interest; generating a diagnostic assessment based on the first regions of interest and the at least one pattern.

Abstract: Techniques for classifying biomedical image data using a graph neural network are disclosed. In one particular embodiment, the techniques may be realized as a method for classifying biomedical image data comprising generating an annotated representation of biomedical image data; identifying a plurality of pixel clusters based on the biomedical image data; constructing a graph based on the plurality of pixel clusters; determining at least one biomedical feature for at least one node of the graph based on the annotated representation of the biomedical image data; and processing a graph neural network to classify the biomedical image data based on the at least one biomedical feature.