Literature DB >> 24743081

Combined model for diabetes lifestyle support.

Peter Gyuk1, Istvan Szabo1, Istvan Vassanyi1, Istvan Kosa1, Levente Kovacs2.   

Abstract

Treatment of diabetes mellitus is a public health related problem of modern healthcare. Surveys show that current methods to estimate the required amount of insulin are quite inefficient in practice as they are based on experience. This paper offers a new approach to predict the glucose level of people with diabetes. It combines two efficient models of the literature: one for nutrient absorption and one for glucose control. The combination of them tracks the blood sugar level considering nutrition composition, applied insulin and initial glucose level. Compared to already existing mixed meal models, the current version takes into account a more detailed nutrition composition (protein, lipid, monosaccharide, fiber and starch) supported by our expert dietary systems. Although the model gives satisfactory results even with parameter sets taken from literature, parameter training by genetic algorithms yields a better tracking of the patients.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24743081

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  1 in total

1.  Artificial Intelligence Methodologies and Their Application to Diabetes.

Authors:  Mercedes Rigla; Gema García-Sáez; Belén Pons; Maria Elena Hernando
Journal:  J Diabetes Sci Technol       Date:  2017-05-25
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.