Abstract
The paper presents a model to analyze data structured in classes, to determine their representativity and classification. The model includes an algorithm integrating three parameters: Informational-Weight, Differential-Weight and Tipicity-Contrast. In application we analyze clinical data on 160 patients with lip and palate malformations. The model allows to assess how representative the sample is, using the variables of the cleft, lip and nose along with some expertly determined comparison criteria. Moreover using the Tipicity-Contrast parameter a supervised classification was achieved and has been able to classify correctly, in average, a 93% of the patients. As a result this model can provide helpful auxiliary criteria in medical decision-making.
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Vega-Alvarado, L., Ortíz-Posadas, M.R. (2014). A Tipicity Concept for Data Analysis and Its Application to Cleft Lip and Palate. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_75
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DOI: https://doi.org/10.1007/978-3-319-12568-8_75
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12567-1
Online ISBN: 978-3-319-12568-8
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