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Authors: C. A. Peña Fernández 1 ; A. B. B. F. Cunha 2 and M. A. Alves 2

Affiliations: 1 Electrotechnical Department at Federal Institute of Bahia, Rod. BR 324, KM 102, Feira de Santana, Brazil ; 2 Computer Science Department at Federal Institute of Bahia, Rod. BR 324, KM 102, Feira de Santana, Brazil

Keyword(s): HIV, Neural Networks, Dynamic Backpropagation, Protease Inhibitors.

Abstract: The present paper uses the learning ability of neural networks (NN) to design a nonlinear model and a nonlinear controller that reduces the number of infected/uninfected CD4+ T cells into the HIV dynamic when an antiviral therapy based on protease inhibitors is applied. The dynamic of the closed-loop system based on such therapy is analyzed to understand the stability of infected/uninfected CD4+ T cells according to a global feedback law that regards un-modeled dynamic terms. To this end, a robust control scheme based on NARMA-L2 approach and a modified version of an already existing dynamic backpropagation algorithm is used to improve the antiviral therapy performance (strongly related to the tracking error). The robustness of the proposed model shows that antiviral therapy performance guarantees less infected CD4+ T cells.

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Paper citation in several formats:
Fernández, C.; Cunha, A. and Alves, M. (2020). NARMA-L2-based Antiviral Therapy for Infected CD4+ T Cells in a Nonlinear Model for HIV Dynamics: Protease Inhibitors-based Approach. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 675-683. DOI: 10.5220/0008980606750683

@conference{icaart20,
author={C. A. Peña Fernández. and A. B. B. F. Cunha. and M. A. Alves.},
title={NARMA-L2-based Antiviral Therapy for Infected CD4+ T Cells in a Nonlinear Model for HIV Dynamics: Protease Inhibitors-based Approach},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2020},
pages={675-683},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008980606750683},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - NARMA-L2-based Antiviral Therapy for Infected CD4+ T Cells in a Nonlinear Model for HIV Dynamics: Protease Inhibitors-based Approach
SN - 978-989-758-395-7
IS - 2184-433X
AU - Fernández, C.
AU - Cunha, A.
AU - Alves, M.
PY - 2020
SP - 675
EP - 683
DO - 10.5220/0008980606750683
PB - SciTePress

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