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104 Control theory in biomedical engineering

Rihan, F.A., Abdelrahman, D.H., Lakshmanan, S., Alkhajeh, A., 2014b. A time delay model
of tumour-immune system interactions: global dynamics, parameter estimation, sensitiv-
ity analysis. Appl. Math. Comput. 232, 606–623.
Rihan, F.A., Hashish, A., Al-Maskari, F., Sheek-Hussein, M., Ahmed, E., Riaz, M.B.,
Yafia, R., 2016. Dynamics of tumor-immune system with fractional-order. J. Tumor.
Res. 2 (1), 109.
Rihan, F.A., Lakshmanan, S., Maurer, H., 2019. Optimal control of tumour-immune model
with time-delay and immuno-chemotherapy. Appl. Math. Comput. 353 (7), 147–165.
Roose, T., Chapman, S., Maini, P., 2007. Mathematical models of avascular tumor growth.
SIAM Rev. 49, 179–208.
Sinek, J., Frieboes, H., Zheng, X., Cristini, V., 2004. Two-dimensional chemotherapy sim-
ulations demonstrate fundamental transport and tumor response limitations involving
nanoparticles. Biomed. Microdevices 6 (4), 297–309.
Smith, S.E., 2005. Optimal control of delay differential equations using evolutionary
algorithms. Complex. Int. 12, 1–10.
Smith, H., 2011. An Introduction to Delay Differential Equations With Applications to the
Life Sciences. Springer, New York, Dordrecht, Heidelberg, London.
Swan, G., 1985. Optimal control applications in the chemotherapy of multiple myeloma.
IMA J. Math. Appl. Med. Biol. 2, 139–160.
Villasana, M., Radunskaya, A., 2003. A delay differential equation model for tumour growth.
J. Math. Biol. 47, 270–294.
WHO, 2018. International Agency for Research on Cancer (IARC). WHO, p. 263.