On the Application of Rough Sets to Skeletal Maturation Classification. Garza-Morales, R., López-Irarragori, F., & Sanchez, R. Artif. Intell. Rev., 45(4):489--508, Kluwer Academic Publishers, Norwell, MA, USA, April, 2016. ![On the Application of Rough Sets to Skeletal Maturation Classification [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Assessment of skeletal maturation is important for the accurate diagnosis and medical treatment of many disorders and syndromes. However, determining skeletal maturation is not a trivial task, and requires professional medical training. The aim of this paper is to review the application of classification techniques to the problem of identifying the skeletal maturation stage of individuals, in order to provide the specialists a second opinion to backup or reject their assessments. A methodology based on Rough Sets is developed, which formulates skeletal maturation as a multicriteria classification problem, and generates classification rules employing data from lateral radiographs. Our methodology introduces the concept of transition maturity stages to obtain a finer classification on the data. Our empirical evaluation shows that the rules generated match the terms used by experts to determine maturation stage. Furthermore, our rough sets methodology produces the best results in our case of study, both in terms of coverage on the data and accuracy of the classification process, with respect to alternative classification approaches.
@article{Garza-Morales:2016:ARS:2903277.2903297,
author = {Garza-Morales, Rodolfo and L\'{o}pez-Irarragori, Fernando and Sanchez, Romeo},
title = {On the Application of Rough Sets to Skeletal Maturation Classification},
journal = {Artif. Intell. Rev.},
issue_date = {April 2016},
volume = {45},
number = {4},
month = apr,
year = {2016},
issn = {0269-2821},
pages = {489--508},
numpages = {20},
url = {http://dx.doi.org/10.1007/s10462-015-9450-x},
doi = {10.1007/s10462-015-9450-x},
acmid = {2903297},
publisher = {Kluwer Academic Publishers},
address = {Norwell, MA, USA},
abstract="Assessment of skeletal maturation is important for the accurate diagnosis and medical treatment of many disorders and syndromes. However, determining skeletal maturation is not a trivial task, and requires professional medical training. The aim of this paper is to review the application of classification techniques to the problem of identifying the skeletal maturation stage of individuals, in order to provide the specialists a second opinion to backup or reject their assessments. A methodology based on Rough Sets is developed, which formulates skeletal maturation as a multicriteria classification problem, and generates classification rules employing data from lateral radiographs. Our methodology introduces the concept of transition maturity stages to obtain a finer classification on the data. Our empirical evaluation shows that the rules generated match the terms used by experts to determine maturation stage. Furthermore, our rough sets methodology produces the best results in our case of study, both in terms of coverage on the data and accuracy of the classification process, with respect to alternative classification approaches.",
keywords = {Machine learning, Multicriteria classification, Rough sets, Skeletal maturation},
}
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