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Cited by in F6Publishing
For: Jarrett AM, Faghihi D, Ii DAH, Lima EABF, Virostko J, Biros G, Patt D, Yankeelov TE. Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities. J Clin Med 2020;9:E1314. [PMID: 32370195 DOI: 10.3390/jcm9051314] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Hormuth DA 2nd, Phillips CM, Wu C, Lima EABF, Lorenzo G, Jha PK, Jarrett AM, Oden JT, Yankeelov TE. Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data. Cancers (Basel) 2021;13:3008. [PMID: 34208448 DOI: 10.3390/cancers13123008] [Reference Citation Analysis]
2 Kuznetsov M, Clairambault J, Volpert V. Improving cancer treatments via dynamical biophysical models. Phys Life Rev 2021;39:1-48. [PMID: 34688561 DOI: 10.1016/j.plrev.2021.10.001] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 Colli P, Gomez H, Lorenzo G, Marinoschi G, Reali A, Rocca E. Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth. Math Models Methods Appl Sci 2021;31:1419-68. [DOI: 10.1142/s0218202521500299] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
4 Kazerouni AS, Gadde M, Gardner A, Hormuth DA 2nd, Jarrett AM, Johnson KE, Lima EABF, Lorenzo G, Phillips C, Brock A, Yankeelov TE. Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology. iScience 2020;23:101807. [PMID: 33299976 DOI: 10.1016/j.isci.2020.101807] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
5 Clairambault J. Stepping From Modeling Cancer Plasticity to the Philosophy of Cancer. Front Genet 2020;11:579738. [PMID: 33329717 DOI: 10.3389/fgene.2020.579738] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Garcke H, Lam KF, Signori A. Sparse Optimal Control of a Phase Field Tumor Model with Mechanical Effects. SIAM J Control Optim 2021;59:1555-80. [DOI: 10.1137/20m1372093] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
7 Lecca P. Control Theory and Cancer Chemotherapy: How They Interact. Front Bioeng Biotechnol 2020;8:621269. [PMID: 33520972 DOI: 10.3389/fbioe.2020.621269] [Reference Citation Analysis]
8 Eastman B, Przedborski M, Kohandel M. Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy. Sci Rep 2021;11:17882. [PMID: 34504141 DOI: 10.1038/s41598-021-97028-6] [Reference Citation Analysis]
9 Henscheid N. Generating patient-specific virtual tumor populations with reaction-diffusion models and molecular imaging data. Math Biosci Eng 2020;17:6531-56. [PMID: 33378865 DOI: 10.3934/mbe.2020341] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
10 Hormuth DA 2nd, Farhat M, Christenson C, Curl B, Chad Quarles C, Chung C, Yankeelov TE. Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy. Adv Drug Deliv Rev 2022;187:114367. [PMID: 35654212 DOI: 10.1016/j.addr.2022.114367] [Reference Citation Analysis]
11 Liu J, Hormuth DA, Yang J, Yankeelov TE. A Multi-Compartment Model of Glioma Response to Fractionated Radiation Therapy Parameterized via Time-Resolved Microscopy Data. Front Oncol 2022;12:811415. [DOI: 10.3389/fonc.2022.811415] [Reference Citation Analysis]
12 Tan PL, Maurer H, Kanesan J, Chuah JH. Optimal Control of Cancer Chemotherapy with Delays and State Constraints. J Optim Theory Appl. [DOI: 10.1007/s10957-022-02046-7] [Reference Citation Analysis]