Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect.

Juan Li,Lanbo Zheng,Xia Li,Jin Huang

doi:10.3389/fpubh.2020.00173

Abstract

Despite the rapid development of science and technology in healthcare, diabetes remains an incurable lifelong illness. Diabetes education aiming to improve the self-management skills is an essential way to help patients enhance their metabolic control and quality of life. Artificial intelligence (AI) technologies have made significant progress in transforming available genetic data and clinical information into valuable knowledge. The application of AI tech in disease education would be extremely beneficial considering their advantages in promoting individualization and full-course education intervention according to the unique pictures of different individuals. This paper reviews and discusses the most recent applications of AI techniques to various aspects of diabetes education. With the information and evidence collected, this review attempts to provide insight and guidance for the development of prospective, data-driven decision support platforms for diabetes management, with a focus on individualized patient management and lifelong educational interventions.

Highlights

Diabetes mellitus (DM) is a long-term chronic disease
Insulin dosage can be calculated using formulas with the following inputs: carbohydrate coefficient, insulin sensitivity coefficient, and data collected from dynamic blood sugar monitoring; Artificial intelligence (AI) technologies have been intensively applied to this aspect of diabetes management to provide better insulin usage support for patients
We have summarized that the most representative applications of artificial intelligence in diabetes education and management (Table 1)

Summary

Introduction

Diabetes mellitus (DM) is a long-term chronic disease. According to recently published data from the International Diabetes Federation, the number of people worldwide suffering from diabetes has reached 451 million [1]. Various educational methods with more or less pros and cons exist, problems such as how to use existing technologies to optimize educated decisions, how to provide patient-specific guidance and individualized management plans, and how to conduct long-term, effective educational intervention for lifelong chronic diseases are the focus of what needs to be addressed by diabetes education.

Results

Conclusion