Cloud-based Diabetic Prediction Framework: Deep Learning Approach

Since Diabetic is one of most common growing disease in the world. Which open the gate for another kind of diseases such as blindness, kidney problems, heart disease and more. Therefore, we need to develop a system the predict diabetic before it happens to people and advise them to avoid it. The system is more than early detection as its prediction. We propose a cloud-based secure framework that integrates traditional machine learning methods with deep neural networks. The system collect patients readings using IoT devices and sensors, where it will be moved securely using public key encryption to cloud storage. Then the prediction algorithm perform on time prediction on the data to see if the patient expected to be diabetic in the future or not. The prediction techniques tested on Pima Indian diabetic dataset from UCI. The result shows that it performs traditional ML methods with accuracy of 98%.