title: Mathematical modeling of malignant ovarian tumors
metadata.name: dc.contributor.author
metadata.value: Goncharova, Anastasiya B.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Kolpak, Eugeny P.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Vil’, Maria Yu.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Abramova, Alina V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Busko, Ekaterina A.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2022-06-23T14:01:21Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2022-06-23T14:01:21Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2022-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Goncharova A. B., Kolpak E. P., Vil’ M. Yu., Abramova A. V., Busko E. A. Mathematical modeling of malignant ovarian tumors. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2022, vol. 18, iss. 1, pp. 120–134.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2022.110
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/36937
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The article explores modeling the development of ovarian cancer, the treatment of this oncologicaldisease
  in women, the assessment of the time to achieve remission, and the assessment
  of the time of the onset of relapse. The relevance of the study is that ovarian cancer is one
  of the most common cancers in women and has the highest mortality rate among all gynecological
  diseases. Modeling the process of the development of the disease makes it possible
  to better understand the mechanism of the development of the disease, as well as the time
  frame of the onset of each stage, as well as the assessment of the survival time. The aim of
  the work is to develop a model of an ovarian tumor. It is based on a model of competition
  between two types of cells: epithelial cells (normal cells) and tumor cells (dividing cells). The
  mathematical interpretation of the competition model is the Cauchy problem for a system
  of ordinary differential equations. Treatment is seen as the direct destruction of tumor cells
  by drugs. The behavior of solutions in the vicinity of stationary points is investigated by the eigenvalues of the Jacobi matrix of the right side of the equations. On the basis of this model,
  the distribution of conditional patients by four stages of the disease is proposed. Biochemical
  processes that stimulate the accelerated growth of the tumor cell population are modeled
  by a factor that allows tumor cells to gain an advantage in a competitive relationship with
  epithelial cells. The spatio-temporal dynamics of an ovarian tumor leads to a modification
  of the competition model due to the introduction of additional factors into it, taking into
  account the presence of increased nutrition of ovarian tumors, the exit of the tumor from the
  plane of the ovary, as well as the effect of treatment on tumor cells. The new model describes
  the interaction conditions with a system of second-order partial differential equations. The
  results of computer modeling demonstrate an assessment of the distribution of conditional
  patients by stages of the disease, the time of onset of relapse, the duration of remission, the
  obtained theoretical results of modeling are compared with the real data.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 18; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: mathematical modeling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: treatment model
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: malignant tumor of the ovary
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: reproductive system
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Mathematical modeling of malignant ovarian tumors
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 120-134.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/36937/1/120-134.pdf
resources.format: Adobe PDF
resources.size: 419,64 kB