Heart Disease Diagnosis by Neural Networks
Khyati Varshney *
Sanskriti University, Mathura, Uttar Pradesh, India.
Mrinal Paliwal
Sanskriti University, Mathura, Uttar Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
In the present time the Mortality rate will be increased all around the world on their daily basis. So the cause for this might possibly be largely ascribe to the developing in the numbers of the patients with the cardiovascular patient’s diseases. To aggravate the cases, many physicians that have been known for the misdiagnosis of the patients announce heart related ailments. In this research paper, the intelligent systems have been designed in which they will help in the successful diagnosis of the forbearing to avoiding misdiagnosis. In the dataset of a UCI stat log of heart disease that will be using in this investigation. The dataset contains 14 attributes which are essential in the diagnosis of the heart diseases. A system is sculpted on the multilayer neural networks trained with convolutional & simulated convolutional neural networks. The identification of 89% was acquired from the testing of the networks.
Keywords: Convolutional neural networks, diseases, diagnosis, machine learning, neural networks