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@article{180884,
        author = {Anush Shinde and Ashwini Pandagale and Shubham Magar and Vishwa Gawai and Ranjit Ghatage and Shah Mohammed Sami Firoz Ahemad},
        title = {Multiple Disease Prediction System Using Machine Learning and Flask Web App},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3922-3932},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180884},
        abstract = {The convergence of healthcare and technology has ushered in a new era of preventive medicine, where early detection of diseases can significantly alter patient outcomes. This paper introduces an advanced web-based disease prediction system developed to assess the risk of three prevalent conditions: heart disease, diabetes, and Parkinson’s disease. Utilizing the Flask web framework and the RandomForestClassifier algorithm, the system integrates machine learning models trained on extensive datasets with an intuitive user interface, enabling individuals to input health metrics and receive immediate risk assessments. 
This initiative aims to bridge the gap between sophisticated predictive analytics and everyday health monitoring, offering a scalable, accessible tool for the public. The system’s architecture is meticulously designed to handle diverse data inputs, process them through robust models, and present results in a comprehensible format, all while maintaining flexibility for future enhancements. 
This document provides an exhaustive exploration of the system’s development process, including its objectives, a thorough review of prior research on disease prediction, detailed module breakdowns, hardware and software prerequisites, potential future directions, and a comprehensive conclusion. By emphasizing early detection and user empowerment, this work contributes to the evolving landscape of digital health solutions, with the potential to reduce the burden of chronic diseases on global populations.},
        keywords = {Flask, Machine Learning, Diabetes, Heart Disease, Parkinson’s Disease, Random Forest Classifier.},
        month = {June},
        }