Paper Title
Artificial Neural Networks Models and Algorithms for Diabetes Disease Diagnosis: A Review

Abstract - Diabetes disease can be considered as one of the major health problem over the world. Diabetes is a condition in which sugar amount in the blood is higher than normal. There is an urgent need to develop efficient systems for diabetes diagnoses according to high health care costs for individuals and hospitals. Artificial Neural Networks (ANNs) were successfully used in image and signal processing systems. Many literature studies were considered ANN approaches and algorithms for classification of the diabetes diseases. The objective of this paper is to review and discuss the studies related to diabetes diagnosis using ANNs. Models, Algorithms, data sets, strengths and limitations of these studies were considered in this paper. Finally, recommendations were suggested for building ANNs methodologies for diabetes classification and diagnosis. Keywords - Diabetes Disease, Artificial Neural Networks (ANNs), Machine Learning, Optimization Algorithms.