Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning

Iman Rezaeian, Eliseos J. Mucaki, Katherina Baranova, Huy Quang Pham, Dimo Angelov, Alioune Ngom, Luis Rueda 0001, Peter K. Rogan. Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning. F1000Research, 5:2124, 2016. [doi]

@article{RezaeianMBPANRR16,
  title = {Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning},
  author = {Iman Rezaeian and Eliseos J. Mucaki and Katherina Baranova and Huy Quang Pham and Dimo Angelov and Alioune Ngom and Luis Rueda 0001 and Peter K. Rogan},
  year = {2016},
  doi = {10.12688/f1000research.9417.1},
  url = {https://doi.org/10.12688/f1000research.9417.1},
  researchr = {https://researchr.org/publication/RezaeianMBPANRR16},
  cites = {0},
  citedby = {0},
  journal = {F1000Research},
  volume = {5},
  pages = {2124},
}