Practical identifiability of mathematical models of biomedical processes

Sergey Kabanikhin, Maktagali Bektemesov, Olga Krivorotko, Zholaman Bektemessov

Результат исследования: Научные публикации в периодических изданияхстатья по материалам конференциирецензирование


The paper is devoted to a numerical study of the uniqueness and stability of problems of determining the parameters of dynamical systems arising in pharmacokinetics, immunology, epidemiology, sociology, etc. by incomplete measurements of certain states of the system at fixed time. Significance of parameters difficult to measure is very high in many areas, as their definition will allow physicians and doctors to make an effective treatment plan and to select the optimal set of medicines. Due to the fact that the problems under consideration are ill-posed, it is necessary to investigate the degree of ill-posedness before its numerical solution. One of the most effective ways is to study the practical identifiability of systems of nonlinear ordinary differential equations that will allow us to establish a set of identifiable parameters for further numerical solution of inverse problems. The paper presents methods for investigating practical identifiability: the Monte Carlo method, the matrix correlation method, the confidence intervals method and the sensitivity based method. There is presented two mathematical models of the pharmacokinetics of the C-peptide and mathematical model of the spread of the COV ID − 19 epidemic. The identifiability investigation will allow us to construct a regularized unique solution of the inverse problem.

Язык оригиналаанглийский
Номер статьи012014
ЖурналJournal of Physics: Conference Series
Номер выпуска1
СостояниеОпубликовано - 20 дек 2021
Событие11th International Scientific Conference and Young Scientist School on Theory and Computational Methods for Inverse and Ill-posed Problems - Novosibirsk, Российская Федерация
Продолжительность: 26 авг 20194 сен 2019

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