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Review
. 2018 May 30;20(5):e10775.
doi: 10.2196/10775.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Ivan Contreras  1 , Josep Vehi  1   2
Affiliations
Review

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Ivan Contreras et al. J Med Internet Res. .

Abstract

Background: Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis.

Objective: The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges.

Methods: A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review.

Results: We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results.

Conclusions: We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life.

Keywords: artificial intelligence; blood glucose; diabetes management; machine learning; mobile computing.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The number of published articles in Google Scholar that include the terms “diabetes” and “artificial intelligence.”.
Figure 2
Figure 2
A taxonomy of some of the best known artificial intelligence methods.
Figure 3
Figure 3
A general diagram of the learning algorithm process.
Figure 4
Figure 4
General CRISP-DM model for the knowledge discoveryin databases (KDD) process.
Figure 5
Figure 5
The case-based reasoning circle.
Figure 6
Figure 6
Summary of the review process and classification of articles into a set of subdomains.
Figure 7
Figure 7
Number of articles reviewed according to subdomain and year of publication (BG: blood glucose).
See this image and copyright information in PMC

References

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