A Hybrid Predictive Model to Detect Heart Attack Possibility Using Artificial Intelligence Algorithms

• Author(s): Oguoma Ikechukwu Stanley ; Uka Kanayo Kizito ; Chukwu Alphonsus Chekwube ; Ikechukwu Peter Amujiogu ; David Osondu Akuchie; Shanice Kristy Archibald
• Paper ID: 1708066
• Page: 1001-1009
• Published Date: 28-04-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 10 April-2025

Abstract

This study was able to further x-ray the power of artificial intelligence once more in providing a leading and more accurate knowledge that could help detect early enough disease progression on time. Heart attack prediction using 299 dataset involving clinical data from two different health sectors in Owerri Municipal council by using a Machine learning software development life circle (ML-SDLC) methodological approach which produced a hybrid model to detect high accuracy on the predicted dataset shows that Random Forest (RF) with validation accuracy of 0.875 =88%, test accuracy 0.881=88% and Out-of-bag accuracy 0.614 = 61% while K-Nearest Neighbors (KNN) with validation accuracy of 0.729 = 73% and test accuracy 0.746 = 75% respectively has attributed death event witnessed in this areas as caused by delay in time for detection of the disease. Evaluation Metrics of all factors, confusion matrices, Roc Curves, Andrews curve, Precision (positive predictive value)/support and the RF out-of-bag result shown in Table 3 and 6 of this paper was able to develop a high percentage rate evaluation result on the two applied algorithms that helped in the development of the heart attack predictive model for disease detection and faster decision making.

Keywords

Artificial Intelligence, Machine Learning, Random Forest and K-Nearest Neighbors (KNN) Classification Models, Heart Attack Prediction Early detection of heart disease

Citations

IRE Journals:
Oguoma Ikechukwu Stanley , Uka Kanayo Kizito , Chukwu Alphonsus Chekwube , Ikechukwu Peter Amujiogu , David Osondu Akuchie; Shanice Kristy Archibald "A Hybrid Predictive Model to Detect Heart Attack Possibility Using Artificial Intelligence Algorithms" Iconic Research And Engineering Journals Volume 8 Issue 10 2025 Page 1001-1009

IEEE:
Oguoma Ikechukwu Stanley , Uka Kanayo Kizito , Chukwu Alphonsus Chekwube , Ikechukwu Peter Amujiogu , David Osondu Akuchie; Shanice Kristy Archibald "A Hybrid Predictive Model to Detect Heart Attack Possibility Using Artificial Intelligence Algorithms" Iconic Research And Engineering Journals, 8(10)