Prognostic medication: prediction by a macroscopic equation model for actual medical histories of illness with various recovery speeds

Aya Hosoi, Tsubasa Takizawa, Remi Konagaya, Ken Naitoh

Research output: Contribution to journalArticle

Abstract

A network theory model based on a nonlinear differential equation (Naitoh in Jpn J Ind Appl Math 28:15-26, 2011a; Proceedings of JSST 2011 international conference on modeling and simulation technology, pp 322–327, b, Naitoh and Inoue in J Artif Life Robot 18:127–132, 2013) macroscopically showed a possibility for explaining interaction mechanism of six groups of molecules on information and function in human beings. In this paper, we show that time-dependent computational results of the number of vigorous cells agreed well with individual medical histories of illness for actual patients. Computational results showed illness with three types of recovery speeds: illness with fast recovery speed having recovery period of several months, with medium speed like leukemia or small cell carcinoma having one or two-year-recovery period, and with low speed having recovery period about five years like the symptom of illness named “anti-N-methyl-d-aspartate (anti-NMDA) receptor encephalitis”. It is stressed that both of the period under unresponsive state in early stage and total years needed to recover cognitive function completely in anti-NMDA receptor encephalitis can be simulated. These results may indicate that the model macroscopically and essentially describes time-dependent activation level of human beings.

Original languageEnglish
Pages (from-to)189-198
Number of pages10
JournalArtificial Life and Robotics
Volume25
Issue number2
DOIs
Publication statusPublished - 2020 May 1

Keywords

  • Evidence
  • Premonition of illness
  • Prognostic medication
  • Recovery speed

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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