Tumor Model Identification and Statistical Analysis

Johanna Sapi, Tamas Ferenci, Daniel Andras Drexler, L. Kovács

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Tumor growth model identification under antiangiogenic therapy is a very current issue since the existing models in the literature have some limitations and usually they are not clinically validated. We have carried out animal experiments to observe valid data, mice were transplanted with C38 colon Aden carcinoma and they were treated with bevacizumab. Two groups were created, control group was treated according to the protocol, while case group members receive much lower doses daily. We created fixed and mixed models for the groups. Mixed models differs from fixed ones in random effects-in the case of mixed models both the intercept and the slope are random variables. These models are appropriate when the aim is to model not the concrete subjects in the sample, but rather, to describe the imagined population from which the samples were coming.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2481-2486
Number of pages6
ISBN (Print)9781479986965
DOIs
Publication statusPublished - Jan 12 2016
EventIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong
Duration: Oct 9 2015Oct 12 2015

Other

OtherIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
CountryHong Kong
CityKowloon Tong
Period10/9/1510/12/15

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Keywords

  • bevacizumab
  • C38 colon adenocarcinoma
  • identification
  • mixed model
  • tumor growth

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Information Systems and Management
  • Control and Systems Engineering

Cite this

Sapi, J., Ferenci, T., Drexler, D. A., & Kovács, L. (2016). Tumor Model Identification and Statistical Analysis. In Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 (pp. 2481-2486). [7379566] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2015.434