Abstract: Histopathological scoring can be based on the areas of certain types of cells or the expression of genotypic or phenotypic characteristics of those cells, as identified by a biological assay. Automating a scoring process with an image analysis algorithm includes correctly delineating the areas of interest, a process known as segmentation. The present systems and methods accomplish this segmentation using a generative adversarial network trained to generate masks covering each area of interest. The invention can perform both segmentation and classification by using a separate image band for each class. A scoring algorithm may utilize the classifications of, for example, a tumor area and an area of immune cell staining by interpreting the separate image bands of each area. Classification problems with more bands would use images with the equivalent number of bands. There is no limit to the number of bands an image can encode for each pixel.

Abstract: Provided is a dynamic label for a product. Data that is generated at different nodes in the supply chain can be linked to a unique identifier associated with the product. At a particular node, the dynamic label may be added to the product, container, or package. The dynamic label may include a Near Field Communication (“NFC”) tag with a value that can be read using a user device. The dynamic label may be connected to the unique identifier. When the product reaches a consumer, the consumer may use a device to read the dynamic label, and pass the value from the dynamic label to a host. The host may identify the connection between the dynamic label and the unique identifier, and may provide the data, that is generated by different nodes in the supply chain and that is associated with the unique identifier, to the user device.