PERSONALIZED DIABETES SUGGESTION USING MACHINE LEARNING AND CLOUD TECHNOLOGY

– Diabetes is a chronic disease that requires continuous monitoring and personalized healthcare support. Traditional healthcare systems are often reactive and fail to provide real-time and individualized recommendations. This paper presents a Personalized Diabetes Suggestion System using Machine Learning and Cloud Technology to improve early detection and management of diabetes. The proposed system utilizes a hybrid model combining Deep Learning and Adaptive Neuro-Fuzzy Inference System (ANFIS) to analyze clinical and lifestyle data such as glucose levels, diet, physical activity, and stress. A cloud-based infrastructure enables scalable data processing and storage, while blockchain technology ensures secure and tamper-proof medical records. The system generates real-time alerts and personalized suggestions for users, improving decision-making and disease management. Experimental results indicate improved prediction accuracy and enhanced user engagement compared to traditional approaches. The proposed solution offers a proactive, secure, and intelligent framework for diabetes care, contributing to better health outcomes and patient empowerment.