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Artificial intelligence in diabetes management: Advancements, opportunities, and challenges
The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialists, uneven distribution of medical resources, low...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591058/ https://www.ncbi.nlm.nih.gov/pubmed/37788667 http://dx.doi.org/10.1016/j.xcrm.2023.101213 |
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author | Guan, Zhouyu Li, Huating Liu, Ruhan Cai, Chun Liu, Yuexing Li, Jiajia Wang, Xiangning Huang, Shan Wu, Liang Liu, Dan Yu, Shujie Wang, Zheyuan Shu, Jia Hou, Xuhong Yang, Xiaokang Jia, Weiping Sheng, Bin |
author_facet | Guan, Zhouyu Li, Huating Liu, Ruhan Cai, Chun Liu, Yuexing Li, Jiajia Wang, Xiangning Huang, Shan Wu, Liang Liu, Dan Yu, Shujie Wang, Zheyuan Shu, Jia Hou, Xuhong Yang, Xiaokang Jia, Weiping Sheng, Bin |
author_sort | Guan, Zhouyu |
collection | PubMed |
description | The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialists, uneven distribution of medical resources, low adherence to medications, and improper self-management contribute to poor glycemic control in patients with diabetes. Recent advancements in digital health technologies, especially artificial intelligence (AI), provide a significant opportunity to achieve better efficiency in diabetes care, which may diminish the increase in diabetes-related health-care expenditures. Here, we review the recent progress in the application of AI in the management of diabetes and then discuss the opportunities and challenges of AI application in clinical practice. Furthermore, we explore the possibility of combining and expanding upon existing digital health technologies to develop an AI-assisted digital health-care ecosystem that includes the prevention and management of diabetes. |
format | Online Article Text |
id | pubmed-10591058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105910582023-10-24 Artificial intelligence in diabetes management: Advancements, opportunities, and challenges Guan, Zhouyu Li, Huating Liu, Ruhan Cai, Chun Liu, Yuexing Li, Jiajia Wang, Xiangning Huang, Shan Wu, Liang Liu, Dan Yu, Shujie Wang, Zheyuan Shu, Jia Hou, Xuhong Yang, Xiaokang Jia, Weiping Sheng, Bin Cell Rep Med Review The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialists, uneven distribution of medical resources, low adherence to medications, and improper self-management contribute to poor glycemic control in patients with diabetes. Recent advancements in digital health technologies, especially artificial intelligence (AI), provide a significant opportunity to achieve better efficiency in diabetes care, which may diminish the increase in diabetes-related health-care expenditures. Here, we review the recent progress in the application of AI in the management of diabetes and then discuss the opportunities and challenges of AI application in clinical practice. Furthermore, we explore the possibility of combining and expanding upon existing digital health technologies to develop an AI-assisted digital health-care ecosystem that includes the prevention and management of diabetes. Elsevier 2023-10-02 /pmc/articles/PMC10591058/ /pubmed/37788667 http://dx.doi.org/10.1016/j.xcrm.2023.101213 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Guan, Zhouyu Li, Huating Liu, Ruhan Cai, Chun Liu, Yuexing Li, Jiajia Wang, Xiangning Huang, Shan Wu, Liang Liu, Dan Yu, Shujie Wang, Zheyuan Shu, Jia Hou, Xuhong Yang, Xiaokang Jia, Weiping Sheng, Bin Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title | Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title_full | Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title_fullStr | Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title_full_unstemmed | Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title_short | Artificial intelligence in diabetes management: Advancements, opportunities, and challenges |
title_sort | artificial intelligence in diabetes management: advancements, opportunities, and challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591058/ https://www.ncbi.nlm.nih.gov/pubmed/37788667 http://dx.doi.org/10.1016/j.xcrm.2023.101213 |
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