Can fractional differentiation improve stability results and data fitting ability of a prostate cancer model under intermittent androgen suppression therapy?

Ozlem Ozturk Mizrak, Cihan Mizrak, Ardak Kashkynbayev, Yang Kuang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we compare the ordinary and fractional versions of a prospective model in the prostate cancer literature to be able to verify the hypothesis that fractional differentiation can improve stability results and data fitting ability of the ordinary version. For that, the mean square error values for androgen and prostate-specific antigen for the first 1.5 cycles of intermittent androgen suppression therapy administered to 62 selected patients from the Vancouver Prostate Center are computed. Stability analyses of the fractional models are also studied and showed how the fractional differentiation contributes to improve the stability results of an ordinary prostate model. Additionally, our findings are supported by PSA and androgen simulations of three different class of patients. Finally, with a conclusion part, which hints for future works should be taken into account are pointed out.

Original languageEnglish (US)
Article number109529
JournalChaos, Solitons and Fractals
Volume131
DOIs
StatePublished - Feb 2020

Keywords

  • Androgen suppression therapy
  • Data fitting
  • Fractional differentiation
  • Prostate cancer
  • Stability

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematics(all)
  • Physics and Astronomy(all)
  • Applied Mathematics

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