To diagnose muscle disease, histopathologic evaluation of muscle biopsy is essential. In addition, since myositis has a well-established treatment, an accurate diagnosis is required. However, distinguishing myositis from other muscle diseases is challenging for pathologists. Thus, artificial intelligence is expected to improve medical productivity. Therefore, we developed an algorithm based on deep convolutional neural networks to make the algorithm for muscle biopsy diagnosis. We used 1,400 hematoxylin-and-eosin-stained pathology slides for training and testing. Our trained algorithm achieved better sensitivity and specificity than the diagnoses made by physicians.