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Pathological examination of tissue has long been used in the diagnosis of disease. However, recent advances in imaging technologies have allowed for us to digitize pathology, which opens new avenues of exploration. Digital pathology not only increases our ability to analyze pathological slides computationally, including using machine learning, to provide diagnostic and theragnostic data, but it also allows for telepathology, increasing collaboration and improving diagnostic capabilities in low-resource areas where such tasks may have previously been unavailable. This digitization also allows us to gather additional data beyond traditional pathological staining, further improving our understanding of disease.
This Collection welcomes original research into digital pathology, including studies examining technologies for digitizing pathology and machine learning techniques for digitized data.