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@article{169693,
        author = {Yash Mishra and Simran Mandal and Sajal Kaushik and Samiksha Upase and Shruti Awatade and Sudhanshu Kawade},
        title = {SMART HEALTHCARE CONSULTATION FOR  CARDIOVASCULAR RISK},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {3820-3823},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169693},
        abstract = {The proposed idea is to create a smart health consultation using machine learning to give accuracy about heart disease risk a patient will have seen before consulting a doctor. The user can achieve the benefit of a smart health consultation only when it can diagnose a kind of disease and provide the necessary information. People nowadays suffer from a variety of heart diseases as a result of the environment and lifestyle choices. The lengthy process for a patient to visit a diagnostic center and consult a doctor. In machine learning approaches it is easy to solve this difficult problem. The user can easily predict the heart disease risk. The true objective is to design a model that can determine heart disease risk, with accuracy.},
        keywords = {Machine Learning Algorithms, Decision Tree Algorithm And Prediction Algorithm.},
        month = {December},
        }