Comparison of Accuracy Rate in Prediction of Cardiovascular …

Emerging


2
Citations
22
Refs
2023
Year
Search Works
Work Details
  • DOI 10.18137/cardiometry.2022.25.15261531
  • OpenAlex ID W4367335937
  • Type Article
  • Language EN
  • Published 14 Feb 2023
  • Pages 1526–1531
  • Source Cardiometry
  • Publisher Russian New University
  • FWCI 0.42
  • Countries 1
  • Institutions 1
  • Added 10 Oct 2025
  • Updated 21 Sep 2026
MENU
0

Comparison of Accuracy Rate in Prediction of Cardiovascular Disease using Random Forest with Logistic Regression

Article 2023 EN Gold

Aim: Comparison of accuracy rate in prediction of cardiovascular disease using Novel Random Forest with Logistic Regression. Materials and Methods: The Novel Random forest (N=20) and Novel Logistic Regression Algorithm (N=20) these two algorithms are calculated by using 2 Groups and taken 20 samples for both algorithm and accuracy in this work.The sample size is determined using the G power Calcul…

2

Citations

22

References

2

Authors

0.42

FWCI

Citations by Year
Last 1 years
Topics
Keywords
UN Sustainable Development Goals
1 SDGs
Authors & Affiliations
2 authors
#AuthorInstitutionsORCID
1 T. Vishnuvardhan Saveetha University (IN) —
2 A. Rama Saveetha University (IN)

Data: OpenAlex