Siket, Máté and Eigner, György and Kovács, Levente (2020) Sensitivity and identifiability analysis of a third-order tumor growth model. In: 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE), 2020.06.02. - 2020.06.04., Budapest, Hungary.
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Abstract
The growing cancer cases attract more and more scientific research and introductions of new models, applied control algorithms and methods. The models are fundamental in the area of computer generated low-dose metronomic (LDM) chemotherapy, when the administration of the drug is ought to be optimized. Generally the in-silico tests and investigations are based on a model, which is hypothesized to describe the given process reliably and accurately. The analysis of the models and its parameters is crucial for therapy generation. We performed an analysis of a third-order tumor growth model based on sensitivity analysis and identifiability tests. The results show that a subset of parameters can be fixed as population values and the rest of the parameter sets results in an identifiable system with minor loss of accuracy.
| Item Type: | Conference or Workshop Item (Paper) |
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| Subjects: | R Medicine / orvostudomány > RC Internal medicine / belgyógyászat > RC0254 Neoplasms. Tumors. Oncology (including Cancer) / daganatok, tumorok, onkológia R Medicine / orvostudomány > RM Therapeutics. Pharmacology / terápia, gyógyszertan T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában |
| Depositing User: | Dr Dániel András Drexler |
| Date Deposited: | 17 Feb 2021 13:04 |
| Last Modified: | 17 Feb 2021 13:04 |
| URI: | http://real.mtak.hu/id/eprint/121221 |
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