Regularized error function-based extended Kalman filter for estimating the cancer chemotherapy dosage: impact of improved grey wolf optimization

• Autorzy: Mohite Utkarsha L. , Patel Hirenkumar G.

Identyfikatory

DOI

10.1515/bams-2020-0048

• Języki publikacji: EN

Abstrakty

EN

Objectives: The main aim of this work is to introduce a robust controller for controlling the drug dosage. Methods: The presented work establishes a novel robust controller that controls the drug dosage and it also carried out parameters estimation. Along with this, a Regularized Error Function-based EKF (REF-EKF) is introduced for estimating the tumor cells that could be adapted for different conditions. It also assists in solving the overfitting problems, which occur during the drug dosage estimation. Moreover, the performance of the adopted controller is compared over other conventional schemes, and the attained outcomes reveal the appropriate impact of drug dosage injection on immune, normal, and tumor cells. It is also ensured that the presented controller does a robust performance on the parameter uncertainties. Moreover, to enhance the performance of the proposed system and for fast convergence, it is aimed to fine-tune the initial state of EKF optimally using a new Improved Gray Wolf Optimization (GWO) termed as Adaptive GWO (AGWO). Finally, analysis is held to validate the betterment of the presented model. Results: The outcomes, the proposed method has accomplished a minimal value of error with an increase in time, when evaluated over the compared models. Conclusions: Thus, the improvement of the proposed REFEKF-AGWO model is proved from the attained results.

Słowa kluczowe

EN

adaptive GWO; chemotherapy; drug dosage; error function; immune; normal cells

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; Index Copernicus Sp. z o.o.
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2021
• Tom: Vol. 17, no. 1
• Strony: 41--54
• Opis fizyczny: Bibliogr. 44 poz., rys., tab.

Twórcy

autor

Mohite Utkarsha L.

• SVNIT, Ichchhanath Surat-Dumas Road, Keval Chowk, Surat, Gujarat, India, 395007

autor

Patel Hirenkumar G.

• SVNIT, Surat, Gujarat, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).