Key result
Novel logistic regression achieves ~98% accuracy for heart disease prediction, beating K-Nearest Neighbor.
Why the study?
Improving accuracy in heart disease prediction using novel logistic regression compared to K-NN algorithm was the study objective.
Does a Novel Logistic Regression model improve accuracy in Heart Disease Prediction compared to a K-Nearest Neighbor Algorithm?
Does a Novel Logistic Regression model improve accuracy in Heart Disease Prediction compared to a K-Nearest Neighbor Algorithm?
Absolute Event Rate: 98.45% vs 79.82%
p-value: p=0.01
A novel logistic regression model demonstrated significantly higher accuracy than a K-nearest neighbor algorithm for heart disease prediction.
Aim: To improve the accuracy in Heart Disease Prediction using Novel Logistic Regression and K-NN Algorithm. Materials and Methods: This study contains 2 groups i.e Novel Logistic Regression and. Each group consists of a sample size of 10 and the study parameters include alpha value 0.01, beta value 0.2, and the Gpower value of 0.8. Results: The Novel Logistic Regression (98.45) achieved improved accuracy than the K-NN Algorithm (79.82) in Heart Disease Prediction. The statistical significance difference is 0.01 (p<0.05). Conclusion: The Novel Logistic Regression model is significantly better than the K-NN Algorithm in Heart Disease Prediction. It can be also considered a better option for Heart Disease Prediction. Keywords Logistic Regression, Novel K-Nearest Neighbor, Heart disease, Artificial Intelligence, Computer Vision.
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Karthi et al. (2023) studied Heart disease (n=20). Novel Logistic Regression vs. K-Nearest Neighbor Algorithm was evaluated on Accuracy in Heart Disease Prediction (p=0.01). Novel Logistic Regression achieved significantly higher accuracy (98.45%) than the K-Nearest Neighbor Algorithm (79.82%) for heart disease prediction (p=0.01).
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