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@article{176184,
        author = {Ms. Aishwarya Rameshwar Dhote and Prof. Santosh S. Mhaske and Dr. C. M. Jadhao},
        title = {Detection of Cardiac Abnormalities Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5888-5891},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176184},
        abstract = {Cardiovascular diseases have become the leading cause of death worldwide over the last few decades, affecting both developed and developing countries. Early detection of cardiac diseases, along with continuous supervision by clinicians, can significantly reduce the mortality rate. However, accurate detection of heart diseases in all cases and 24-hour patient consultations by doctors are often not feasible due to the demands of time and expertise. The medical field is witnessing notable advancements through machine learning techniques, which have improved the accuracy of cardiac disease predictions. This methodology actively aims to highlight significant factors associated with heart disease. This study employs the Random Forest (RF) classification algorithm to train the model.},
        keywords = {Cardiac disease, Machine learning, Random Forest},
        month = {April},
        }