Cardiac Arrest Prediction using Machine Learning Algorithms. Issue 6 (July 2021)

• Record Type: Journal Article
• Authors: Karthikeyan, R; Vijendra Babu, D.; EKarthik, ; Suresh, R.; Nalathambi, M; Dinakaran, S.
• Is Part Of: Journal of physics. Volume 1964:Issue 6(2021)
• Publication Date: 2021-07
• Subjects: Cardiac arrest -- diagnosis -- medical supporting systems -- machine learning algorithms; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1964/6/062076
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Cardiac arrest and other cardiovascular problems are the most prevalent issue among millions of men, and there are numerous causes that function as the basis of this crisis, such as people's wellbeing, mainly because of job stress, exhaustion, bad food quality, and an elevated cholesterol level as a consequence of the lack of technology cardiac disease. Many scientific and medical support programs change every day, yet every program has its own special features, advantages and disadvantages. The goal of this article is to research the probability of cardiac arrest based on various regulated or unregulated variables in specific data set machine learning algorithms.