A related convolutional neural network for cancer diagnosis using microRNA data classification

Abstract This paper develops a method for cancer classification from microRNA data using a convolutional neural network (CNN)‐based model optimized by genetic algorithm. The convolutional neural network has performed well in various recognition and perception tasks. This paper contributes to the cancer classification using a union of two CNNs. The method’s performance is boosted by the relationship between CNNs and exchanging knowledge between them. Besides, communication between small sizes of CNNs reduces the need for large size CNNs and, consequently,