Cardiovascular health pre-diagnosis based on a BP profile using Artificial Neural Network

This study describes the implementation of Artificial Neural Network Pattern Recognition using Back-Propagation algorithm which can perform cardiovascular health pre-diagnosis of a patient through a generated blood pressure profile. The proponents gathered data from institutions that conduct Exercise Stress Testing, specifically the Treadmill Stress Test. The data gathered were age, gender, height, weight, blood pressure and heart rate readings and is considered as blood pressure condition risk factor. They compose the 47 input parameters of the network and was then divided into two - the training data and the testing data. This was put into a database created using Microsoft Excel. The back-propagation neural network model gives an accurate pre-diagnosis. The trained system gives an acceptable pre-diagnosis in reference to the given diagnosis by the attending practitioner that facilitated the collection of data.