Cyber-Physical-Human Systems in Precision Medicine: Advances in Artificial Pancreas for Treatment of Diabetes
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View abstract on PubMed
Summary
This summary is machine-generated.Cyber-physical-human systems (CPHS) leverage digital twins for type 1 diabetes (T1D) management. This AI-powered artificial pancreas automates insulin delivery, improving patient outcomes and reducing disease burden.
Area Of Science
- Biomedical Engineering
- Artificial Intelligence in Medicine
- Computational Physiology
Background
- Cyber-physical-human systems (CPHS) offer transformative potential in chronic disease management, particularly for diabetes.
- Advances in artificial intelligence (AI) have accelerated the application of digital twins in healthcare.
- Digital twins of individuals with type 1 diabetes (T1D) and the pancreas can model complex disease processes.
Purpose Of The Study
- To develop an AI-enabled automated insulin delivery system using digital twins for T1D management.
- To create accurate digital twins by integrating mechanistic and data-driven models.
- To demonstrate the system's capability for real-time, automated treatment decisions in precision medicine.
Main Methods
- A hybrid modeling framework combining mechanistic physiological and data-driven empirical models was developed.
- Digital twins of individuals with T1D were created using this framework.
- The digital twins were integrated into an AI-enabled automated insulin delivery system (artificial pancreas).
Main Results
- The developed hybrid model accurately represents T1D metabolic, physiologic, and pharmacologic processes.
- The AI-enabled CPHS successfully automated insulin delivery, mitigating glucose homeostasis disturbances.
- Simulations and clinical experiments validated the system's performance in real-time precision medicine.
Conclusions
- Digital twins and AI-driven CPHS represent a significant advancement in T1D treatment.
- Automated insulin delivery systems improve patient outcomes and reduce the burden of T1D.
- Future research should focus on online learning, adaptive systems, and cybersecurity for enhanced CPHS.
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