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Computational techniques to monitoring fractional order type-1 diabetes mellitus model for feedback design of artificial pancreas.

Muhammad FarmanAli HasanChangjin XuKottakkaran Sooppy NisarEvren Hincal
Published in: Computer methods and programs in biomedicine (2024)
In the model under investigation, parametric uncertainties are identified since the glucose, insulin, and glucagon system's parameters are accurately measured numerically at different fractional order values. In terms of algorithm resilience and Caputo tracking in the presence of glucagon and insulin intake disturbance to maintain the glucose level. A comprehensive analysis of numerous difficult test issues is conducted in order to offer a thorough justification of the planned strategy to control the type 1 diabetes mellitus with designed the artificial pancreas.
Keyphrases
  • glycemic control
  • blood glucose
  • type diabetes
  • machine learning
  • climate change
  • cardiovascular risk factors
  • deep learning
  • social support
  • insulin resistance
  • adipose tissue
  • metabolic syndrome
  • skeletal muscle