Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

被引:65
|
作者
Guan, Zhouyu [1 ]
Li, Huating [1 ]
Liu, Ruhan [1 ,2 ,3 ]
Cai, Chun [1 ]
Liu, Yuexing [1 ]
Li, Jiajia [1 ,2 ]
Wang, Xiangning [4 ]
Huang, Shan [1 ,2 ]
Wu, Liang [1 ]
Liu, Dan [1 ]
Yu, Shujie [1 ]
Wang, Zheyuan [1 ,2 ]
Shu, Jia [1 ,2 ]
Hou, Xuhong [1 ]
Yang, Xiaokang [2 ]
Jia, Weiping [1 ]
Sheng, Bin [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Med 6, Shanghai Peoples Hosp, Shanghai Clin Ctr Diabet,Shanghai Int Joint Lab In, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, MOE Key Lab AI, Shanghai 200240, Peoples R China
[3] Natl Engn Res Ctr Personalized Diagnost & Therapeu, Furong Lab, Changsha, Hunan, Peoples R China
[4] Shanghai Jiao Tong Univ, Affiliated Peoples Hosp 6, Dept Ophthalmol, Shanghai 200233, Peoples R China
关键词
DEEP LEARNING ALGORITHM; CHRONIC KIDNEY-DISEASE; NEURAL-NETWORK; RISK-FACTORS; RETINOPATHY; MELLITUS; PREDICTION; CLASSIFICATION; TECHNOLOGY; OUTCOMES;
D O I
10.1016/j.xcrm.2023.101213
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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 world-wide. A shortage of diabetes specialists, uneven distribution of medical resources, low adherence to medi-cations, 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.
引用
收藏
页数:20
相关论文
共 50 条
  • [31] Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors
    Vettoretti, Martina
    Cappon, Giacomo
    Facchinetti, Andrea
    Sparacino, Giovanni
    SENSORS, 2020, 20 (14) : 1 - 18
  • [32] Artificial intelligence application in the diagnosis and treatment of bladder cancer: advance, challenges, and opportunities
    Ma, Xiaoyu
    Zhang, Qiuchen
    He, Lvqi
    Liu, Xinyang
    Xiao, Yang
    Hu, Jingwen
    Cai, Shengjie
    Cai, Hongzhou
    Yu, Bin
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [33] Artificial intelligence and public sector human resource management in South Africa: Opportunities, challenges and prospects
    Chilunjika, Alouis
    Intauno, Kudakwashe
    Chilunjika, Sharon R.
    SA JOURNAL OF HUMAN RESOURCE MANAGEMENT, 2022, 20
  • [34] Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities
    Christou, Chrysanthos D.
    Tsoulfas, Georgios
    WORLD JOURNAL OF GASTROINTESTINAL ONCOLOGY, 2022, 14 (04) : 765 - 793
  • [35] Opportunities and challenges for the application of artificial intelligence paradigms into the management of endemic viral infections: The example of Chronic Hepatitis C Virus
    Farrag, Ahmed N.
    Kamel, Ahmed M.
    El-Baraky, Iman A.
    REVIEWS IN MEDICAL VIROLOGY, 2024, 34 (02)
  • [36] Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect
    Li, Juan
    Huang, Jin
    Zheng, Lanbo
    Li, Xia
    FRONTIERS IN PUBLIC HEALTH, 2020, 8
  • [37] Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities
    Du, Shuili
    Xie, Chunyan
    JOURNAL OF BUSINESS RESEARCH, 2021, 129 : 961 - 974
  • [38] Artificial Intelligence and Filipino Academic Librarians: Perceptions, Challenges and Opportunities
    de Leon, Lady Catherine R.
    Flores, Lejempf V.
    Alomo, Anna Rita L.
    JOURNAL OF THE AUSTRALIAN LIBRARY AND INFORMATION ASSOCIATION, 2024, 73 (01) : 66 - 83
  • [39] Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study
    Xiao, Ningkun
    Huang, Xinlin
    Wu, Yujun
    Li, Baoheng
    Zang, Wanli
    Shinwari, Khyber
    Tuzankina, Irina A.
    Chereshnev, Valery A.
    Liu, Guojun
    FRONTIERS IN MEDICINE, 2025, 12
  • [40] Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities
    Flynn, Connor D.
    Chang, Dingran
    DIAGNOSTICS, 2024, 14 (11)