Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts : WestminsterResearch

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Title	Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts
Authors	Soria, D. and Garibaldi, J.M.
Type	Conference paper
Abstract	Recent studies in breast cancer domains have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a variety of unsupervised learning techniques. Consensus among the clustering algorithms has been used to categorise patients into these specific groups, but often at the expenses of not classifying all patients. It is known that fuzzy methodologies can provide linguistic based classification rules to ease those from consensus clustering. The objective of this study is to present the validation of a recently developed extension of a fuzzy quantification subsethood-based algorithm on three sets of newly available breast cancer data. Results show that our algorithm is able to reproduce the seven biological classes previously identified, preserving their characterisation in terms of marker distributions and therefore their clinical meaning. Moreover, because our algorithm constitutes the fundamental basis of the newly developed Nottingham Prognostic Index Plus (NPI+), our findings demonstrate that this new medical decision making tool can help moving towards a more tailored care in breast cancer.
Keywords	Rule-based classification, Fuzzy rules, Validation, Breast cancer
Year	2016
Conference	IEEE International Conference on Machine Learning and Applications (ICMLA2016)
Publisher	IEEE
Accepted author manuscript	Soria_ICMLA2016_Camera_Ready.pdf
Published	02 Feb 2017
Journal citation	pp. 576-581
Book title	Machine Learning and Applications (ICMLA), 2016 15th IEEE International Conference on
ISBN	9781509061679
Funder	University of Nottingham
Digital Object Identifier (DOI)	https://doi.org/10.1109/ICMLA.2016.0101

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Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts

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