Web-Based Framework for the Prediction of Type 1 Diabetes in Youth Using EHR’s Data

The study proposed a predictive model for evaluating the risk of Type 1 diabetes in individuals aged 5–30 using an easily navigable web platform available in many regional languages, including Hindi, Marathi, Bangla, and Kannada. The web page's default language is English. The suggested methodology determines the patient's risk of Type 1 diabetes by compiling the symptoms that they independently describe. The suggested framework achieves a maximum accuracy of 94% and an average accuracy of 89%. The platform facilitates user interaction and basic data entry, hence ensuring accessibility for users with varying linguistic backgrounds. The research investigation demonstrates the efficacy of the strategy in promoting early detection, which pushes preventative healthcare measures. Customized risk assessments are provided by the system, which focuses on a variety of symptoms. The importance of early intervention and better patient outcomes is emphasized in the study. This work aligns well with the expanding area of healthcare analytics and offers a useful tool for preventative health initiatives. The multilingual platform addresses the common health problem of Type 1 diabetes in children and young people while improving user engagement and adaptability.