## Appendix A
(2023) [PERSON]; [PERSON]; [PERSON] Optimal Administration Strategy in Chemotherapy Regimens Using Multi-Drug Cell-Cycle Specific Tumor Growth Models. _Biomed. Signal Process Control_**2023**, _86_, 105221. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Multiple Model Predictive Control for Optimal Drug Administration of Mixed Immunotherapy and Chemotherapy of Tumours. _Comput. Methods Programs Biomed._**2017**, _144_, 13-19. [CrossRef]
* [PERSON] (2024) [PERSON]; [PERSON] [PERSON] On the Optimal Control Problem for a Model of the Synergy of Chemo- and Immunotherapy. _Optim. Control Appl. Methods_**2024**, _45_, 575-593. [CrossRef]
* [PERSON] et al. (2024) [PERSON]; [PERSON]; [PERSON] [PERSON] Bang-Bang Optimal Controls for a Mathematical Model of Chemo- and Immunotherapy in Cancer. _Discret. Contin. Dyn. Syst. B_**2024**, _29_, 1481-1500. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] A Mathematical Model of Tumor Growth and Its Response to Single Irradiation. _Theor. Biol. Med. Model._**2016**, _13_, 6. [CrossRef]
* [PERSON] et al. (2011) [PERSON]; [PERSON]; [PERSON] Robustness of Optimal Controls for a Class of Mathematical Models for Tumor Anti-Angiogenesis. _Math. Biosci. Eng._**2011**, \(8\), 355-369. [CrossRef]
* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] [PERSON] Combination of Antiangiogenic Treatment with Chemotherapy as a Multi-Input Optimal Control Problem. _Math. Methods Appl. Sci._**2022**, _45_, 3058-3082. [CrossRef]
* [PERSON] et al. (2011) [PERSON]; [PERSON]; [PERSON] [PERSON] Optimal and Suboptimal Protocols for a Mathematical Model for tumor Anti-Angiogenesis in Combination with Chemotherapy. _Math. Biosci. Eng._**2011**, \(8\), 307-323. [CrossRef] [PubMed]
* [PERSON] et al. (2009) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Nonlinear Modelling of Cancer: Bridging the Gap between Cells and Tumours. _Nonlinearity_**2009**, _23_, R1. [CrossRef] [PubMed]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors. _Pharmacol. Syst. Pharmacol._**2019**, \(8\), 720-737. [CrossRef]
* [PERSON] and [PERSON] (2016) [PERSON]; [PERSON] Employing Dynamical Computational Models for Personalizing Cancer Immunotherapy. _Expert. Opin. Biol. Ther._**2016**, _16_, 1373-1385. [CrossRef]* [PERSON] et al. (2023) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] TGM-Nets: A Deep Learning Framework for Enhanced Forecasting of Tumor Growth by Integrating Imaging and Modeling. _Eng. Appl. Artif. Intell._**2023**, _126_, 106867. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Machine Learning in Oncological Pharmacogenomics: Advancing Personalized Chemotherapy. _Funct. Integr. Genom._**2022**, _24_, 182. [CrossRef]
* [PERSON] and [PERSON] (2025) [PERSON]; [PERSON]; [PERSON] Integrating Machine Learning to Customize Chemotherapy for Oral Cancer Patients. _Oral. Oncol. Rep._**2025**, _13_, 100711. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Comparing Methods for Parameter Estimation of the Gompertz Tumor Growth Model. _IFAC-PapersOnLine_**2017**, _50_, 12203-12209. [CrossRef]
* [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Tumor Growth Modeling: Parameter Estimation with Maximum Likelihood Methods. _Comput. Methods Programs Biomed._**2018**, _160_, 1-10. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Tracking Parameter Changes of an Impulsive Tumor Growth Model. In Proceedings of the 2022 IEEE 10 th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems (ICCC), Reykjavik, Iceland, 6-9 July 2022; pp. 179-184. * [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] The Effect of the Choice of Initial Estimation for a Tumor Model Parameter Estimation Problem.