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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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.
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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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