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@article{186755,
        author = {Riddhesh Gujarathi and Atharva Pandhare and Shruti Ray and Sanika Chavhan and Prof. Rinku Badgujar},
        title = {Health and Fitness Report Analyzer: An AI-Based System for Disease Prediction and Personalized Diet Recommendation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {2558-2565},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186755},
        abstract = {The growing use of digital diagnostics in modern healthcare produces a vast amount of medical data that most individuals find difficult to interpret on their own. Laboratory indicators such as glucose, cholesterol, and vitamin levels provide essential insights into a person’s health, yet their complexity often prevents early detection of potential issues. This paper presents the Health and Fitness Report Analyzer, an intelligent system powered by artificial intelligence that interprets health-report parameters, forecasts possible risks of lifestyle-related illnesses, and suggests personalized nutritional plans. The framework integrates multiple machine-learning algorithms—Random Forest, XGBoost, and Logistic Regression—to evaluate the likelihood of conditions such as anemia, diabetes, and cardiovascular disease. In addition, Explainable AI (XAI) methods like SHAP are utilized to provide interpretability by revealing the influence of each parameter on model outcomes. The system transforms intricate numerical results into clear, user-friendly insights and tailored wellness guidance, encouraging proactive and data-driven healthcare management.},
        keywords = {Artificial Intelligence, Machine Learning, Explainable AI, Predictive Health Analytics, Personalized Diet Recommendation.},
        month = {November},
        }