Abstract: A DRGs automatic grouping method based on convolutional neural network, including: collecting case data and grouping according to a major diagnostic broad categories and core diagnosis-related grouping method; performing numerical coding to the data; constructing a shallow convolutional neural network model, using a k-means clustering method to cluster the feature vectors extracted from the convolutional network to obtain k category labels, combining the category labels and classifier to supervise the network performing iterative training; after finishing training the model, perform data grouping application. The method of the present disclosure is used to avoid the disadvantages of manual feature selection and additional data labeling for adding new grouping categories, automatic learning grouping can be performed for data with vague and difficult groupings.