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@article{175929,
        author = {Sai Priya R and Sarin Priya D},
        title = {DIABETICS DETECTION USING PYTHON},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4367-4372},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175929},
        abstract = {Diabetes is a significant global health issue that necessitates early diagnosis and management to prevent severe complications. The project aims to develop a web based application using Flask and machine learning to predict the likelihood of diabetes. Users input specific health parameters such as age, BMI, glucose levels, and insulin levels through a user-friendly web interface. The backend, powered by Flask, processes these inputs using a pre-trained machine learning model (e.g., Random Forest Classifier) to provide instant predictions. The application includes robust security measures to ensure the privacy and confidentiality of user data. Additionally, it logs user inputs and prediction results to continuously improve the model's accuracy. The system architecture involves a responsive front-end, a Flask based backend, and a secure database for storing user data. This approach facilitates early diagnosis and timely management, potentially improving health outcomes and providing a valuable tool for both individuals and healthcare providers.},
        keywords = {},
        month = {April},
        }