Stability Analysis and Numerical Approach to Chemotherapy Model for the Treatment of Lung Cancer

This paper introduces and examines a mathematical model aimed at understand- ing the efficacy of chemotherapy in treating lung cancer. Through the utilization of differential equations, we delve into the intricate interplay between healthy cells, tumor cells, damaged tumor cells, and the impact of chemotherapy. Our analytical deductions are substantiated through extensive numerical simulations, revealing the profound effectiveness of chemotherapy in curbing tumor progression. Addition- ally, stability analysis is discussed and numerical simulations are suggested for the model that we have presented. These findings not only contribute significantly to the realm of lung cancer research but also hold substantial promise for therapeutic advancements. Moreover, the insights gleaned from this study are poised to enrich educational endeavors pertaining to lung cancer modeling, thereby fostering a deeper understanding of its underlying dynamics and treatment strategies.

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Publication Details

Journal
International Journal of Computational and Experimental Science and Engineering
Published
2025-03-04
DOI
https://doi.org/10.22399/ijcesen.1095
Citations
1
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
1.37
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article

Stability Analysis and Numerical Approach to Chemotherapy Model for the Treatment of Lung Cancer

E. Vargees Kaviyan, S. Sujitha, T. Jayakumar, R. Ilakkiya
1 citations
International Journal of Computational and Experimental Science and Engineering
Mathematical Biology Tumor Growth
1.37
article

Stability Analysis and Numerical Approach to Chemotherapy Model for the Treatment of Lung Cancer

E. Vargees Kaviyan, S. Sujitha, T. Jayakumar, R. Ilakkiya
article en
1 citations

Abstract

This paper introduces and examines a mathematical model aimed at understand- ing the efficacy of chemotherapy in treating lung cancer. Through the utilization of differential equations, we delve into the intricate interplay between healthy cells, tumor cells, damaged tumor cells, and the impact of chemotherapy. Our analytical deductions are substantiated through extensive numerical simulations, revealing the profound effectiveness of chemotherapy in curbing tumor progression. Addition- ally, stability analysis is discussed and numerical simulations are suggested for the model that we have presented. These findings not only contribute significantly to the realm of lung cancer research but also hold substantial promise for therapeutic advancements. Moreover, the insights gleaned from this study are poised to enrich educational endeavors pertaining to lung cancer modeling, thereby fostering a deeper understanding of its underlying dynamics and treatment strategies.

International Journal of Computational and Experimental Science and EngineeringVol. 11(1)
Orthopaedic Research Group (IN), KPR Institute of Engineering and Technology (IN), Ramakrishna Mission Vidyalaya (IN)
Openalex Percentile: Top 25%
Mathematical Biology Tumor Growth
1.37
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