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<p>Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial intelligence (AI) improves diabetes management, diagnosis, and prevention. AI-powered tools enable early detection of diabetes and its complications, including diabetic retinopathy, using sophisticated algorithms and large-scale data analysis. Wearable devices and continuous glucose monitors, integrated with AI, facilitate personalized treatment plans and real-time insights, improving glycemic control and overall health outcomes. Advanced machine learning models demonstrate high accuracy in diagnosing and predicting diabetes, while automated insulin delivery systems and bolus calculators enhance insulin management, reducing risks of hypo- and hyperglycemia. Despite these advancements, challenges such as cost, accessibility, device interoperability, and ethical considerations persist. The development of new digital biomarkers, individualized clinical metrics, and patient-centric solutions is critical for optimizing care. While AI holds immense promise in alleviating the global diabetes burden, addressing these limitations through sustained innovation and collaboration is essential. This review underscores the transformative potential of AI in revolutionizing diabetes care, enabling advancement for enhanced prevention, precise diagnosis, and effective management strategies.</p>

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Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care

  • 期刊论文

  • 发表日期：

    2025年5月30日

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  • Madhav Kohli,
  • Pallavi Pandey,
  • Vikash Jakhmola,
  • Supriyo Saha,
  • Meenu Chaudhary,
  • Arif Nur Muhammad Ansori,
  • Arvind Negi

摘要

Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial intelligence (AI) improves diabetes management, diagnosis, and prevention. AI-powered tools enable early detection of diabetes and its complications, including diabetic retinopathy, using sophisticated algorithms and large-scale data analysis. Wearable devices and continuous glucose monitors, integrated with AI, facilitate personalized treatment plans and real-time insights, improving glycemic control and overall health outcomes. Advanced machine learning models demonstrate high accuracy in diagnosing and predicting diabetes, while automated insulin delivery systems and bolus calculators enhance insulin management, reducing risks of hypo- and hyperglycemia. Despite these advancements, challenges such as cost, accessibility, device interoperability, and ethical considerations persist. The development of new digital biomarkers, individualized clinical metrics, and patient-centric solutions is critical for optimizing care. While AI holds immense promise in alleviating the global diabetes burden, addressing these limitations through sustained innovation and collaboration is essential. This review underscores the transformative potential of AI in revolutionizing diabetes care, enabling advancement for enhanced prevention, precise diagnosis, and effective management strategies.