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Elsevier, Neural Networks, 5-6(18), p. 808-817

DOI: 10.1016/j.neunet.2005.06.023

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Modelling ordinal relations with SVMs: An application to objective aesthetic evaluation of breast cancer conservative treatment

Journal article published in 2005 by Jaime S. Cardoso ORCID, Joaquim F. Pinto da Costa, Maria J. Cardoso
This paper is available in a repository.
This paper is available in a repository.

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Abstract

The cosmetic result is an important endpoint for breast cancer conservative treatment (BCCT), but the verification of this outcome remains without a standard. Objective assessment methods are preferred to overcome the drawbacks of subjective evaluation. In this paper a novel algorithm is proposed, based on support vector machines, for the classification of ordinal categorical data. This classifier is then applied as a new methodology for the objective assessment of the aesthetic result of BCCT. Based on the new classifier, a semi-objective score for quantification of the aesthetic results of BCCT was developed, allowing the discrimination of patients into four classes.