Using FDG-PET Acquired During the Course of Radiation Therapy to Individualize Adaptive Radiation Dose Escalation in Patients with Non-Small Cell Lung Cancer

By F. Kong, G. Kalemkerian, T. Lawrence, C. Pan, R. T. Haken, K. Frey, D. Arenberg, J. Moran, D. Lubman, N. Ramnath. 2010

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Huan-Hsin Tseng
2. Yi Luo
3. Sunan Cui
4. R. T. Ten Haken
5. Jen-Tzung Chien
6. I. E. El Naqa
7. M. Feng

Citations in the corpus

• Deep Reinforcement Learning for Automated Radiation Adaptation in Lung Cancer (2017, methodology): “To achieve this goal, we design the following setup for dose adaptation of NSCLC patients and test its performance using data from a successful dose escalation protocol UMCC 2007-123 [2]-[3].”