Diagnosis of Cardio-Vascular Diseases using Convolutional Neural Network

Abstract

Due to its increasing incidence, cardiovascular globally, depression has become a health issue. The focus of this paper using the early convolutional neural network to construct a framework of early warning (CNN). Systolic blood pressure (SBP) and diastolic blood pressure( DBP) levels were more significantly related to cardiovascular disease than those of pulse pressure. A potential percentage of cardiovascular disease-related mortality was associated with robust elevations of SBP and DBP for both age groups of men. Higher SBP and lower DBP (discordant elevations) also led to a higher risk of cardiovascular disease-related mortality among men aged approximately 46 to 60 years. CNN can reduce the risk factor of blood and pulse pressure. CNN has many more advantages when compared to other neural networks. The paper describes a new method, which is widely used, called Convolutional Neural Network(CNN). Using CNN, the cardiovascular disease which affects old age people and heart patients can easily predict the disease symptoms and can cure the diseases. Nowadays, old age people are suffering from cardiovascular. For these people, this Convolutional neural network will be very useful. Using this CNN method, doctors and nurses can predict disease symptoms accurately and efficiently. There are so many diseases cured by the CNN method. Cardiovascular disease using CNN can cure many heart patients. This article describes to us, how cardiovascular disease, SBP, and DBP can be cured using the CNN method which gives many more positive tracks to the patients.