Cardiovascular disease is one of the most challenging diseases in middle-aged and older people, which causes high mortality. Coronary artery disease (CAD) is known as a common cardiovascular disease. A standard clinical tool for diagnosing CAD is angiography. The main challenges are dangerous side effects and high angiography costs. Today, the development of artificial intelligence-based methods is a valuable achievement for diagnosing disease. Hence, in this paper, artificial intelligence methods such as neural network (NN), deep neural network (DNN), and Fuzzy C-Means clustering combined with deep neural network (FCM-DNN) are developed for diagnosing CAD on a cardiac magnetic resonance imaging (CMRI) dataset. The original dataset is used in two different approaches. First, the labeled dataset is applied to the NN and DNN to create the NN and DNN models. Second, the labels are removed, and the unlabeled dataset is clustered via the FCM method, and then, the clustered dataset is fed to the DNN to create the FCM-DNN model. By utilizing the second clustering and modeling, the training process is improved, and consequently, the accuracy is increased. As a result, the proposed FCM-DNN model achieves the best performance with a 99.91% accuracy specifying 10 clusters, i.e., 5 clusters for healthy subjects and 5 clusters for sick subjects, through the 10-fold cross-validation technique compared to the NN and DNN models reaching the accuracies of 92.18% and 99.63%, respectively. To the best of our knowledge, no study has been conducted for CAD diagnosis on the CMRI dataset using artificial intelligence methods. The results confirm that the proposed FCM-DNN model can be helpful for scientific and research centers.
翻译:心血管疾病是99岁中老年人中最具挑战性的疾病之一,导致高死亡率。冠状动脉疾病(CAD)被称为常见心血管疾病。诊断心血管疾病(CAD)的标准临床工具是血管造影。主要挑战是危险的副作用和高血管造影成本。今天,开发人工智能方法是诊断疾病的宝贵成就。因此,在本文件中,人工智能方法,如神经网络(NNN)、深入的内脏网络(DNNN)和Fuzzy C-Means集群,加上深神经网络(FCM-DNN),被称为常见心血管疾病疾病(CM-DNNN)。诊断标准临床工具是用来诊断心脏磁共振成像(CMRI)数据集的标准。首先,将标签数据集应用到NNND和DNNND来创建NN和D模型模型。第二,通过FCM方法,取消标签标签,将无标签数据集解到FCM方法,第二个数据集成型模型,通过 DNNM数据模型和F数据结果,通过D进行10的升级。