A Type-2 Diabetes Prediction System Using Deep Neural Network Model
Keywords:
Type 2 diabetes, Diabetes early prediction, Machine Learning (ML), Deep Learning (DL).Abstract
Recently, diabetes is the most common chronic disease in the Kingdom of Saudi Arabia, affecting a high percentage of the population. In general, the diabetic disease may be the cause of kidney failure, blindness, and lower-limb amputations. Therefore, the early diagnose of diabetic disease is an essential task to save human lives. On the other hand, the revolution of Artificial Intelligence (AI) approaches has played significant roles in diverse aspects, where Machine Learning (ML) and Deep Learning (DL) methods present a central role in the early prediction of diabetic disease in early stages. This paper aims to research the recent developed AI-based type-2 diabetes prediction systems and analyse their efficiency in terms of classification accuracy. In addition, an efficient AI-based system is presented, analysed, and discussed, for the purpose of diagnosing type-2 diabetes among adults in early stages, based on the employment of an efficient Neural Network (NN) model. The developed system has been validated using two different diabetes datasets for the purpose of assessing the model’s efficiency.
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