Recent advancements using machine learning & deep learning approaches for diabetes detection: a systematic review

Abstract

Nowadays, Diabetes Mellitus is one of the significant health challenges that affects many people across the world. Early detection of Diabetes Mellitus will help in preventing complications, i.e., kidney disease, nerve damage, eye damage, etc. Over the past few years, several Machine Learning and Deep Learning techniques have been applied for the early detection of Diabetes Mellitus. The paper provides reviews on various Machine Learning and Deep Learning techniques applied for early detection of Diabetes mellitus. The review criteria mainly focus on five topics: the diabetes dataset, methods used, performance metrics, limitations of the work, and the overall status of diabetic research. The objective of this paper is to provide a comprehensive review of Diabetes Mellitus prediction techniques applying Machine Learning and Deep Learning that will be helpful sources for researchers in the healthcare field.

Keywords

• Diabetes mellitus
• Glucose
• Diabetic symptoms
• TYpe 2 diabetes mellitus
• Deep learning
• Diabetes Management