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Diabetes Prediction and Management System

Final year students of Shri Madhwa Vadiraja Institute of Technology and Management who are studing in Computer Science and Engineering Aaron Sharon Dsouza, Dhrishya Shetty Missbah Banu Muneer and Peter Caetano Joao are working on a multifaceted diabetes prediction and management system, employing two distinct methodologies:

One based on fasting and postprandial blood sugar levels, and the other incorporating additional health parameters like glucose levels, blood pressure, BMI, and age, utilizing logistic regression. Evaluation of both approaches demonstrated robust predictive capabilities. A user-friendly website interface facilitates seamless data input, enhancing accessibility for users. Complementing predictive features, an online community platform was established to foster peer support and information exchange among individuals managing diabetes, promoting a sense of community and shared experience. Moreover, the system generates personalized diet plans tailored to users’ diabetes status, providing actionable dietary guidance to support health management goals. By integrating predictive analytics, user engagement, and personalized dietary support, our system aims to empower individuals with diabetes, facilitating better health outcomes and fostering a supportive environment for effective disease management. This project is guided by Mrs. Chaitra Bhat M, Assistant Professor of CSE department.