HEART DISEASE PREDICTION USING MACHINE LEARNING ALGORITHMS: A COMPARATIVE STUDY OF LOGISTIC REGRESSION AND KNN - Pareek, Prashun; Kumari, Nidhi; Yadav, Pinky (International Journal of Research -GRANTHAALAYAH, 2025)
This research presents a heart disease prediction system aimed at identifying individuals at risk based on their medical history. With the rising incidence of heart-related conditions, early diagnosis is essential for timely intervention. The system utilizes machine learning algorithms, specifically Logistic Regression and K-Nearest Neighbors (KNN), to classify patients as likely or unlikely to develop heart disease. Experimental results demonstrate improved prediction accuracy compared to traditional methods like Naïve Bayes. The proposed model not only enhances diagnostic precision but also contributes to cost-effective and efficient healthcare. The implementation is provided in .pynb format for practical usability.