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@article{196366,
        author = {D. Kanaka Satya and M. Geetha Priyanka and M. Pavan Kumar and M. Saranya Dheepthi and N. Tejaswi},
        title = {Heart Disease Risk Factor Analysis Using Patient Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {3245-3249},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196366},
        abstract = {heart disease is one of the leading causes of mortality worldwide. Early identification of risk factors is essential for preventive healthcare and effective medical decision-making. This study presents a comprehensive analysis of heart disease risk factors using patient medical data through data science techniques and machine learning models.
A publicly available dataset was collected and pre-processed to ensure data quality. Exploratory Data Analysis (EDA) and statistical correlation techniques were used to identify relationships between key health parameters such as age, blood pressure, cholesterol level, and heart rate. In addition to statistical analysis, multiple machine learning classification models including Logistic Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Gradient Boosting, and Naïve Bayes were implemented. Model performance was evaluated using accuracy, precision, recall, and ROC-AUC metrics. Among the models, Random Forest achieved the best performance and was selected as the optimal model. The trained model was integrated into a web-based application that allows users to input patient data and obtain real-time risk predictions.
The results demonstrate that combining data analysis with machine learning provides an effective approach for understanding and predicting heart disease risk.},
        keywords = {Correlation, Analysis, Data Visualization, Exploratory Data Analysis, Heart Disease,	Machine Learning, Patient Data, Prediction, Risk Factor Analysis.},
        month = {April},
        }