Logistic Regression and KNN Algorithm Experimental Diagnosis to Reduce the Impact of Cardiac Arrest

Kannan Ramaamy (Rathinam College of Arts and Science, Coimbatore, India); Vasanthi V (Karpagam University, India)

Occurrences of many current diseases can rapidly increase in comparison to prehistoric periods. These diseases are generally hazardous to human lives, one of which is notably the cardiovascular disease. Many medical studies have been conducted with developing related technologies, but despite progress early detection and remedies for cardiovascular diseases remain challenging to the medical sector and physicians. Nonetheless, by using machine learning techniques physicians would be able to accurately predict and diagnose symptoms of pending cardiovascular disease. This paper describes our study, wherein the use of various patient data sets and three key machine learning algorithms help medical professionals appraise and visualize the most precise information relating to heart patients, and also provides vital pre-diagnostic data, as well as information about nearby hospitals, all of which can help to save the patient's life.

Journal: International Journal of Simulation- Systems, Science and Technology- IJSSST V20

Published: Feb 27, 2019

DOI: 10.5013/IJSSST.a.20.01.17