| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 8220308 | International Journal of Radiation Oncology*Biology*Physics | 2014 | 7 Pages |
Abstract
These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are expected through a nonlinear combination of multiple features, eventually helping in the task of personalized treatment planning.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Radiation
Authors
Rainer J. PhD, Michael MD, Steffen MD, Karin MD, Iris MD, Ute MD, Richard MD, Ursula MD, Meinhard MD, Sabine MD, Florian MD, Andrea MD, Nicolaus MD, Matthias MD,