Pathologists Look Forward to a Future with Deep Learning and Neural Networks

One of the breast cancer samples from the Tumor Proliferation Assessment Challenge 2016 training data set. Deep learning and neural networks are making significant progress in identifying cancer mitosis. A critical step in the diagnosis of cancer is the analysis of a patient’s biopsy tissue sample, which sometimes can be as small as a pinhead. Even with such a small sample, pathologists can test for the absence or presence of tumor cells to provide important information pertaining to the course of treatment to doctors. To analyze the samples, pathologists typically stain the tissue sample with liquid re-agents. The intensity and distribution of the color stain classify and determine the extent of the disease. The stained tissue samples are then studied under a microscope, which can take long hours, particularly when reviewing…


Link to Full Article: Pathologists Look Forward to a Future with Deep Learning and Neural Networks

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