David A. Hormuth, II

Research Scientist | Biomedical Engineering + Imaging Science > > Computational Oncology

Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.


Journal article


E. Lima, J. Oden, B. Wohlmuth, A. Shahmoradi, D. Hormuth, T. Yankeelov, L. Scarabosio, T. Horger
Computer Methods in Applied Mechanics and Engineering, 2017

Semantic Scholar DOI PubMed
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APA   Click to copy
Lima, E., Oden, J., Wohlmuth, B., Shahmoradi, A., Hormuth, D., Yankeelov, T., … Horger, T. (2017). Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data. Computer Methods in Applied Mechanics and Engineering.


Chicago/Turabian   Click to copy
Lima, E., J. Oden, B. Wohlmuth, A. Shahmoradi, D. Hormuth, T. Yankeelov, L. Scarabosio, and T. Horger. “Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.” Computer Methods in Applied Mechanics and Engineering (2017).


MLA   Click to copy
Lima, E., et al. “Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.” Computer Methods in Applied Mechanics and Engineering, 2017.


BibTeX   Click to copy

@article{e2017a,
  title = {Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.},
  year = {2017},
  journal = {Computer Methods in Applied Mechanics and Engineering},
  author = {Lima, E. and Oden, J. and Wohlmuth, B. and Shahmoradi, A. and Hormuth, D. and Yankeelov, T. and Scarabosio, L. and Horger, T.}
}


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