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

*この研究の対応する著者

研究成果: Article査読

抄録

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.

本文言語English
ページ(範囲)189-198
ページ数10
ジャーナルArtificial Life and Robotics
25
2
DOI
出版ステータスPublished - 2020 5月 1

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能

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