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Cancer is one of the leading causes of death across the world, and early detection of cancer will greatly increase the chances of successful treatment. Histopathology diagnosis of cancer is crucial because most diagnoses of malignancy are made by pathological confirmation. In Japan, lack of pathologist has become a serious problem. The lack of pathologists to diagnose the huge amounts of pathological images has resulted the late of medical diagnosis thus delaying the necessary treatment for the patients. Recently, there has been extensive research work on how to incorporate artificial intelligence in the diagnosis process. For example, using convolutional neural networks (CNN) for histopathologic cancer detection can not only speed up diagnosis but also can increase the diagnosis accuracy. In this study, we consider EfficientNet-B6 CNN model for histopathologic cancer detection and apply different activation …