Future horizons in diabetes: integrating AI and personalized care.

Journal: Frontiers in endocrinology
PMID: 40213102

Abstract

Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditional markers like HbA1c are insufficient for capturing short-term glycemic fluctuations, leading to the need for more precise metrics such as Glucose Variability (GV) and Time in Range (TIR). Continuous Glucose Monitoring (CGM) and AI integration offer real-time data analytics and personalized treatment plans, enhancing glycemic control and reducing complications. The combination of transcutaneous auricular vagus nerve stimulation (taVNS) with artificial Intelligence (AI) further optimizes glucose regulation and addresses comorbidities. Empowering patients through AI-driven self-management and community support is crucial for sustainable improvements. Future horizons in diabetes care must focus on overcoming challenges in data privacy, algorithmic bias, device interoperability, and equity in AI-driven care while integrating these innovations into healthcare systems to improve patient outcomes and quality of life.

Authors

  • Kaiqi Zhang
    National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), College of Engineering, Huazhong Agricultural University, Wuhan, China.
  • Yun Qi
    Rehabilitation Department, Naval Qingdao Special Service Rehabilitation Center, Qingdao, China.
  • Wenjun Wang
    College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, China.
  • Xinyi Tian
    School of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Jiahui Wang
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China.
  • Lili Xu
    Graduate School of Chinese Academy of Traditional Chinese Medicine, Beijing, China.
  • Xu Zhai
    Wangjing Hospital of China Academy of Traditional Chinese Medicine, Beijing, China.

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