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@article{162402,
        author = {Dr. Bhagyashri R Hanji and Deeksha K B and Devon Stephen Fernandes and Dhiraj Athreya H and Drushadwathi B Salian},
        title = {Sports Injury Recovery Period Prediction Based on Injury Type and Diet Plan},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {10},
        pages = {251-256},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162402},
        abstract = {Athletic injuries pose a significant challenge, hindering optimal performance and prolonging rehabilitation. To address this issue, we propose a comprehensive approach to predicting injury recovery duration for sports professionals using machine learning techniques. Our primary goal is to develop a predictive model that accurately forecasts recovery periods based on various factors, including injury type, severity, athlete demographics, medical history, and rehabilitation protocols. Utilizing a comprehensive dataset of historical injury records and performance metrics from a diverse range of athletes across various sports, the model aims to capture complex relationships and enhance prediction accuracy.},
        keywords = {Scoped Session, Cross-validation, One-Hot Encoding, Support Vector Regressor (SVR), Dynamic HTML Rendering, PostgreSQL.},
        month = {},
        }