Paper Title

AI-Based Heart Disease Prediction and Intelligent Alert System Using Ensemble Learning

Authors

Sanjay Gandhi .A , Pranesh Raj .S , Pavithra .L

Keywords

Cardiovascular,Ensemble,XGBoost,UCI

Abstract

Heart diseases account for a large number of global mortalities and there is a necessity for the development of intelligent and interpretable heart disease early-warning systems. This paper proposes a predictive and early warning system for heart diseases utilizing AI that uses ensemble learning applied to 918 patient records of heart diseases from the UCI Machine Learning Repository. There will be a total of six different models used for benchmarking and comparison, Logistic Regression, Random Forest, XGBoost, LightGBM, CatBoost and MLP Neural Networks. Three interaction-based indicators (Blood Pressure - Heart Rate Ratio, Cholesterol – Age and Stress Index) will be designed and incorporated for representing interaction among significant variables. Hyperparameters of both Random Forest and XGBoost will be optimised using RandomisedSearchCV. The ensemble of XGBoost, Logistic Regression, and Random Forest models achieves a maximal accuracy of around 90 percent and an area under the receiver operating curve (RO

How To Cite

"AI-Based Heart Disease Prediction and Intelligent Alert System Using Ensemble Learning", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.d208-d214, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604421.pdf

Issue

Volume 4 Issue 4, April-2026

Pages : d208-d214

Other Publication Details

Paper Reg. ID: JETNR_234072

Published Paper Id: JETNR2604421

Downloads: 00029

Research Area: Science and Technology

Country: Dindigul, , Tamil Nadu, India

Published Paper PDF: https://rjpn.org/JETNR/papers/JETNR2604421

Published Paper URL: https://rjpn.org/JETNR/viewpaperforall?paper=JETNR2604421

About Publisher

ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: RJPN (IJPublication) Janvi Wave

Article Preview