Personalized Diabetes Suggestion Using ML Algorithms and Cloud Technology

Machine learning, a field of artificial intelligence that enables systems to learn from data patterns and make decisions with minimal human intervention, forms the core of this initiative. This initiative provides personalized diabetes management at minimal cost by integrating machine learning and cloud computing. Many people today develop diabetes due to stressful jobs and unhealthy lifestyles, and the condition often goes undetected until it has significantly progressed. Early detection and personalized monitoring, especially for type 2 diabetes, can prevent complications. Our system uses machine learning algorithms such as SVM, ANN, Decision Tree, and Ensemble methods to predict diabetes risk and provide tailored suggestions based on patient data. The cloud-based architecture facilitates data storage and real-time monitoring, promoting proactive disease management.