Type 2 Diabetes Diagnoses and Tracking Mobile Application

Abstract

Diabetes is becoming more common worldwide, demanding careful management to prevent health hazards. Machine Learning will be used to construct a complete software that can categorise people as diabetic or not using many health markers. This endeavour aims to enhance diabetics’ well-being and preventative treatment. The study has numerous objectives. A strong Machine Learning Classifier is proposed to identify diabetics from non-diabetics based on health parameters. Precision health categorisation technology may improve diabetes care. The application envisages the integration of a Step Count Tracker within the application framework. This component is crucial for diabetes therapy since it accurately tracks and documents physical activity. A thorough Calorie Calculator improves the app. This software provides calorie information to aid healthy eating. This tool helps users manage their nutritional intake to promote healthy eating. Finally, the research will develop a Hybrid Method that combines algorithms for application efficiency and precision. This novel strategy may raise the bar for health categorisation applications by enhancing performance and accuracy. These innovative traits make this initiative a health management technology lighthouse. It pioneers proactive diabetes control and combines technology and healthcare to make society healthier.