Abstract
The paper analyzes the cardiovascular parameters of patients with heart disease. The aim of this study was to predict death in a patient with cardiovascular disease based on 12 parameters, using Random Forest and Logistic Regression algorithms. Parameters were tuned for both algorithms to determine the best settings. The most significant factors in the process predicted were found using the FEATURE SELECTION method of both algorithms. By comparative analysis of the obtained results, the highest accuracy of 90% was obtained using the Random Forest Algorithm.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IOP Conference Series: Materials Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.