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@article{188988,
        author = {Abhay Dahe and Rutwik Pawar and Yogesh borse},
        title = {Intelligent Risk Prediction Cardiovascular Diseases Using ML},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {4335-4336},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188988},
        abstract = {cardiovascular diseases (CVDs) are among the leading causes of mortality worldwide and represent a serious challenge to modern healthcare systems. These diseases often develop silently and are diagnosed only after severe complications occur. Early prediction of cardiovascular risk can significantly reduce mortality by enabling timely medical intervention and lifestyle modification. With the rapid growth of electronic health records and medical datasets, machine learning techniques have become effective tools for analyzing complex clinical data and identifying hidden risk patterns. This paper proposes an intelligent machine learning–based system for predicting cardiovascular disease risk using patient health parameters such as age, gender, blood pressure, cholesterol level, blood sugar, heart rate, and other related indicators. The dataset is preprocessed through data cleaning, normalization, and feature selection to improve data quality and model performance. Multiple machine learning algorithms including Logistic Regression, Decision Tree, and Random Forest are implemented and evaluated using accuracy, precision, recall, F1-score, and confusion matrix metrics. Experimental results demonstrate that the Random Forest algorithm achieves superior performance compared to other classifiers. The proposed system provides a reliable, cost-effective, and scalable decision-support tool that can assist healthcare professionals in early diagnosis and preventive cardiovascular care.},
        keywords = {Cardiovascular Disease, Machine Learning, Risk Prediction, Healthcare Analytics, Random Forest},
        month = {December},
        }