A quantifier-based fuzzy classification system for breast cancer patients

@article{Soria2013AQF,
  title={A quantifier-based fuzzy classification system for breast cancer patients},
  author={Daniele Soria and Jonathan Mark Garibaldi and Andrew Russell Green and Des Powe and Christopher C. Nolan and Christophe Lemetre and Graham R. Ball and Ian O. Ellis},
  journal={Artificial intelligence in medicine},
  year={2013},
  volume={58 3},
  pages={
          175-84
        }
}
OBJECTIVES Recent studies of breast cancer data have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a range of different clustering techniques. Consensus between unsupervised classification algorithms has been successfully used to categorise patients into these specific groups, but often at the expenses of not classifying the whole set. It is known that fuzzy methodologies can provide linguistic based classification rules. The objective of this… CONTINUE READING
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