Combining multiple models to generate consensus: application to radiation-induced pneumonitis prediction.

@article{Das2008CombiningMM,
  title={Combining multiple models to generate consensus: application to radiation-induced pneumonitis prediction.},
  author={Shiva K. Das and Shifeng Chen and Joseph O. Deasy and Sumin Zhou and Fang-Fang Yin and Lawrence B. Marks},
  journal={Medical physics},
  year={2008},
  volume={35 11},
  pages={5098-109}
}
The fusion of predictions from disparate models has been used in several fields to obtain a more realistic and robust estimate of the "ground truth" by allowing the models to reinforce each other when consensus exists, or, conversely, negate each other when there is no consensus. Fusion has been shown to be most effective when the models have some complementary strengths arising from different approaches. In this work, we fuse the results from four common but methodologically different… CONTINUE READING

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