[Current applications and challenges of artificial intelligence in diabetes management].

In recent years, the rapid development of artificial intelligence (AI) has brought innovative opportunities to diabetes management, with significant application potential in various aspects such as prevention, screening, diagnosis, and treatment of diabetes. Through big data analysis, AI can achieve precise diabetes sub-typing and further promote personalized treatment. In terms of complication screening, AI can efficiently identify diabetic retinopathy, aiding in early diagnosis and treatment of complications. Combined with continuous glucose monitoring technology, AI can remotely assist in diabetes management through various novel glucose monitoring metrics and algorithms. The AI-based closed-loop insulin pump can automatically adjust insulin infusion, increasing glucose time in range and reducing the risk of hypoglycemia. However, this technological wave is also accompanied by multiple challenges: data privacy disputes, insufficient algorithm interpretability, and delays in clinical validation, which hinder its widespread clinical applications. While AI demonstrates high efficiency in supporting clinical decision-making, complex case management and psychological care should still be dominated by physicians. In the future, the "physician+AI" collaborative pattern will combine humanistic care with technology to optimize diabetes management together.

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Publication Details

Journal
PubMed
Published
2025-04-15
DOI
https://doi.org/10.3760/cma.j.cn112137-20250205-00253
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

[Current applications and challenges of artificial intelligence in diabetes management].

Jinhua Cai, Jian Zhou, Liqun Zhang
PubMed
Artificial Intelligence in Healthcare
article

[Current applications and challenges of artificial intelligence in diabetes management].

Jinhua Cai, Jian Zhou, Liqun Zhang
article en

Abstract

In recent years, the rapid development of artificial intelligence (AI) has brought innovative opportunities to diabetes management, with significant application potential in various aspects such as prevention, screening, diagnosis, and treatment of diabetes. Through big data analysis, AI can achieve precise diabetes sub-typing and further promote personalized treatment. In terms of complication screening, AI can efficiently identify diabetic retinopathy, aiding in early diagnosis and treatment of complications. Combined with continuous glucose monitoring technology, AI can remotely assist in diabetes management through various novel glucose monitoring metrics and algorithms. The AI-based closed-loop insulin pump can automatically adjust insulin infusion, increasing glucose time in range and reducing the risk of hypoglycemia. However, this technological wave is also accompanied by multiple challenges: data privacy disputes, insufficient algorithm interpretability, and delays in clinical validation, which hinder its widespread clinical applications. While AI demonstrates high efficiency in supporting clinical decision-making, complex case management and psychological care should still be dominated by physicians. In the future, the "physician+AI" collaborative pattern will combine humanistic care with technology to optimize diabetes management together.

PubMedVol. 105(15)
Shanghai Jiao Tong University (CN), Shanghai Sixth People's Hospital (CN)
Artificial Intelligence in Healthcare
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[Current applications and challenges of artificial intelligence in diabetes management]. — Jinhua Cai, Jian Zhou, et al. · PubMed (2025) | TGRS Research Map | TGRS