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
  • [1] Artificial Intelligence in Diabetes Mellitus Prediction: Advancements and Challenges - A Review
    Awasthi, Rohit
    Mahavar, Anjali
    Shah, Shraddha
    Patel, Darshana
    Patel, Mukti
    Shah, Drashti
    Patel, Ashish
    CURRENT BIOINFORMATICS, 2024,
  • [2] Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities
    Baker, Stephanie
    Xiang, Wei
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2023, 25 (02): : 1261 - 1293
  • [3] Application of artificial intelligence in wearable devices: Opportunities and challenges
    Nahavandi, Darius
    Alizadehsani, Roohallah
    Khosravi, Abbas
    Acharya, U. Rajendra
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2022, 213
  • [4] Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges
    Huang, Shigao
    Yang, Jie
    Fong, Simon
    Zhao, Qi
    CANCER LETTERS, 2020, 471 : 61 - 71
  • [5] Artificial intelligence and diabetes technology: A review
    Gautier, Thibault
    Ziegler, Leah B.
    Gerber, Matthew S.
    Campos-Nanez, Enrique
    Patek, Stephen D.
    METABOLISM-CLINICAL AND EXPERIMENTAL, 2021, 124
  • [6] Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities
    Sabry, Farida
    Labda, Wadha
    Erbad, Aiman
    Malluhi, Qutaibah
    IEEE ACCESS, 2020, 8 : 175840 - 175858
  • [7] Opportunities and Challenges for Artificial Intelligence Applications in Infrastructure Management During the Anthropocene
    Markolf, Samuel A.
    Chester, Mikhail, V
    Allenby, Braden
    FRONTIERS IN WATER, 2021, 2
  • [8] Artificial Intelligence for Management Information Systems: Opportunities, Challenges, and Future Directions
    Stoykova, Stela
    Shakev, Nikola
    ALGORITHMS, 2023, 16 (08)
  • [9] Artificial intelligence in dermatology: advancements and challenges in skin of color
    Fliorent, Rebecca
    Fardman, Brian
    Podwojniak, Alicia
    Javaid, Kiran
    Tan, Isabella J.
    Ghani, Hira
    Truong, Thu M.
    Rao, Babar
    Heath, Candrice
    INTERNATIONAL JOURNAL OF DERMATOLOGY, 2024, 63 (04) : 455 - 461
  • [10] Revolutionising Acute Cardiac Care With Artificial Intelligence: Opportunities and Challenges
    Doolub, Gemina
    Khurshid, Shaan
    Theriault-Lauzier, Pascal
    Lapalme, Alexis Nolin
    Tastet, Olivier
    So, Derek
    Langlais, Elodie Labrecque
    Cobin, Denis
    Avram, Robert
    CANADIAN JOURNAL OF CARDIOLOGY, 2024, 40 (10) : 1813 - 1827