Optimized drug regimen and chemotherapy scheduling for cancer treatment using swarm intelligence
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-021-04234-6.pdf
Reference18 articles.
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2. Bazrafshan, N., & Lotfi, M. M. (2020). A finite-horizon Markov decision process model for cancer chemotherapy treatment planning: an application to sequential treatment decision making in clinical trials. Annals of Operations Research, 295(1), 483–502. https://doi.org/10.1007/s10479-020-03706-5
3. Bray, F., Jemal, A., Grey, N., Ferlay, J., & Forman, D. (2012). Global cancer transitions according to the human development index (2008–2030): A population-based study. The Lancet Oncology, 13(8), 790–801.
4. Clerc, M., & Kennedy, J. (2002). The particle swarm—explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, 6(1), 58–73. https://doi.org/10.1109/4235.985692
5. de Pillis, L. G., Gu, W., Fister, K. R., & Head, T.a., Maples, K., Murugan, A., Neal, T., & Yoshida, K. (2007). Chemotherapy for tumors: An analysis of the dynamics and a study of quadratic and linear optimal controls. Mathematical Biosciences, 209(1), 292–315.
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