Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Diabetes Management

Background:

• Diabetes is a global pandemic requiring advanced management strategies.
• Artificial intelligence (AI) applications are expanding within the healthcare system.
• Metabolic disorders and diabetes complications necessitate innovative solutions.

Purpose of the Study:

• To provide a comprehensive overview of AI applications in diabetes management.
• To explore AI's role in the diagnosis, treatment, and prevention of diabetes.
• To identify current challenges and future potential of AI in diabetes care.

Main Methods:

• Literature search conducted on PubMed.
• Review of studies integrating AI in diabetes diagnosis, treatment, and management.
• Analysis of AI and machine learning approaches for disease prediction and prevention.

Main Results:

• AI algorithms can visualize large datasets and generate predictions for diabetes.
• AI-powered tools, including mobile apps and automated insulin delivery systems, can reduce patient burden.
• AI aids in identifying disease markers and risk factors for diabetes.
• Machine learning can help limit diabetes prevalence in high-risk areas.

Conclusions:

• AI holds significant potential for improving patient outcomes in diabetes care through personalized treatment.
• Addressing challenges such as privacy, data security, bias, and transparency is crucial for successful AI integration.
• AI and machine learning are vital for managing the global diabetes pandemic effectively.