Metastasis Modelling Approaches—Comparison of Ideas
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-38430-1_16
Reference14 articles.
1. Barbolosi, D., Benabdallah, A., Hubert, F., Verga, F.: Mathematical and numerical analysis for a model of growing metastatic tumors. Math. Biosci. 218(1), 1–14 (2009). https://doi.org/10.1016/j.mbs.2008.11.008
2. Benzekry, S.: Mathematical analysis of a two-dimensional population model of metastatic growth including angiogenesis. J. Evol. Equ. 11(1), 187–213 (2010). https://doi.org/10.1007/s00028-010-0088-5
3. Benzekry, S.: Mathematical and numerical analysis of a model for anti-angiogenic therapy in metastatic cancers. ESAIM: Math. Model. Numer. Anal. 46(2), 207–237 (2011). https://doi.org/10.1051/m2an/2011041.
4. Bilous, M., Serdjebi, C., Boyer, A., Tomasini, P., Pouypoudat, C., Barbolosi, D., Barlesi, F., Chomy, F., Benzekry, S.: Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer. Sci. Rep. 9(1) (2019). https://doi.org/10.1038/s41598-019-49407-3.
5. Haaf, K., Aalst, C.M., Koning, H.J., Kaaks, R., Tammemägi, M.C.: Personalising lung cancer screening: an overview of risk-stratification opportunities and challenges. Int. J. Cancer 149(2), 250–263 (2021). https://doi.org/10.1002/ijc.33578
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