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Intelligent technology-driven diabetes prevention and control: From informatization management to artificial

Geer Deng1, Wang Chengshi2

  • 1Faculty of Arts and Social Sciences, University of Sydney, Sydney, NSW, Australia.

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Intelligent technologies like artificial intelligence are transforming diabetes care. This review explores advances in information management and AI for better diabetes treatment and reduced costs.

Keywords:
Diabetesartificial intelligencediagnosisinformatization managementprecision prevention

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Area of Science:

  • Endocrinology and Metabolic Diseases
  • Medical Informatics
  • Artificial Intelligence in Healthcare

Background:

  • Diabetes mellitus presents a significant global health burden due to rising prevalence and complications.
  • Suboptimal medical care and self-management strategies worsen diabetes outcomes, especially in developing nations.
  • Advancements in intelligent technologies offer potential solutions to improve diabetes treatment efficiency and reduce costs.

Purpose of the Study:

  • To conduct a narrative review of research on information management and artificial intelligence in diabetes care.
  • To discuss the opportunities and challenges associated with the clinical translation and application of these technologies.
  • To provide a conceptual framework for future intelligent diabetes care research and development.

Main Methods:

  • A narrative literature review was performed.
  • The review followed the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines.
  • Research advances from information management to artificial intelligence in diabetes were synthesized.

Main Results:

  • Intelligent technologies, including information management systems and AI, show promise in enhancing diabetes treatment efficiency.
  • These technologies have the potential to reduce the costs associated with diabetes management.
  • The review identified key opportunities and challenges for clinical implementation.

Conclusions:

  • Intelligent technologies represent a paradigm shift in diabetes management, moving towards more efficient and cost-effective care.
  • Successful clinical translation requires addressing identified challenges.
  • This review provides a framework to guide future research and development in intelligent diabetes care.