Abstract
According to the clinical results from Manrique et. al. [1], a breast cancer immunotherapy model is established. The model is established based on biological principles and limited clinical results [1] for replications and prognostics of therapeutic effects. A single objective parametric optimization problem is formulated to find appropriate parameter values with biological meanings. Several constraints are formulated to satisfy both the disease progression without treatments and bio-system stability and equilibrium. To solve this parametric optimization problem with constraints automatically, the ϵ-DE+NSGA-II algorithm is proposed. The constraint violation is the second objective to be optimized in NSGA-II. The proposed ϵ-DE+NSGA-II can find the optimal parameters of the cancer immunotherapy model. The cancer immunotherapy model with the optimized parameters can not only replicate the clinical results from [1], but also provide prognostic outcomes for tumor rejection under various drug delivery schedules.
| Original language | English |
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| Title of host publication | 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings |
| Publisher | IEEE |
| ISBN (Electronic) | 9781538627259, 9781538627266 |
| ISBN (Print) | 9781538627273, 9781538640586 |
| DOIs | |
| Publication status | Published - Dec 2017 |
| Event | 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017) - Hilton Hawaiian Village Waikiki Resort, Honolulu, Hawaii, United States Duration: 27 Nov 2017 → 1 Dec 2017 http://ieee-ssci.org http://www.ele.uri.edu/ieee-ssci2017/index.html |
Conference
| Conference | 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017) |
|---|---|
| Abbreviated title | IEEE SSCI 2017 |
| Place | United States |
| City | Honolulu, Hawaii |
| Period | 27/11/17 → 1/12/17 |
| Internet address |
