Artificial Intelligence in Current Diabetes Management and Prediction
Purpose of Review Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanied...
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Published in | Current diabetes reports Vol. 21; no. 12; p. 61 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.12.2021
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | Purpose of Review
Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanied by the dramatic improvement in computer performance. In this review, we introduce AI/ML-based medical devices and prediction models regarding diabetes.
Recent Findings
In the field of diabetes, several AI-/ML-based medical devices and regarding automatic retinal screening, clinical diagnosis support, and patient self-management tool have already been approved by the US Food and Drug Administration. As for new-onset diabetes prediction using ML methods, its performance is not superior to conventional risk stratification models that use statistical approaches so far.
Summary
Despite the current situation, it is expected that the predictive performance of AI will soon be maximized by a large amount of organized data and abundant computational resources, which will contribute to a dramatic improvement in the accuracy of disease prediction models for diabetes. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 |
ISSN: | 1534-4827 1539-0829 |
DOI: | 10.1007/s11892-021-01423-2 |