Existing work demonstrates the value of image-based cardiovascular diagnosis with AI. We aimed to develop and test a machine learning algorithm for cardiovascular disease classification based on cine image datasets of 570 consecutive patients. Disease classification was performed using a random forest (RF) classifier and a disease classification network based on graph attention networks. The fully automated deep learning algorithm showed high accuracy for cardiac disease classification based on cine images only. Such algorithm has the potential to improve the efficiency of the reading process, especially by identifying and filtering out patients with normal cardiac anatomy and function.