Feature Selection for Better Identification of Subtypes of Guillain-Barré Syndrome
Joint Authors
Hernández-Torruco, José
Canul-Reich, Juana
Frausto-Solís, Juan
Méndez-Castillo, Juan José
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-14
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Guillain-Barré syndrome (GBS) is a neurological disorder which has not been explored using clustering algorithms.
Clustering algorithms perform more efficiently when they work only with relevant features.
In this work, we applied correlation-based feature selection (CFS), chi-squared, information gain, symmetrical uncertainty, and consistency filter methods to select the most relevant features from a 156-feature real dataset.
This dataset contains clinical, serological, and nerve conduction tests data obtained from GBS patients.
The most relevant feature subsets, determined with each filter method, were used to identify four subtypes of GBS present in the dataset.
We used partitions around medoids (PAM) clustering algorithm to form four clusters, corresponding to the GBS subtypes.
We applied the purity of each cluster as evaluation measure.
After experimentation, symmetrical uncertainty and information gain determined a feature subset of seven variables.
These variables conformed as a dataset were used as input to PAM and reached a purity of 0.7984.
This result leads to a first characterization of this syndrome using computational techniques.
American Psychological Association (APA)
Hernández-Torruco, José& Canul-Reich, Juana& Frausto-Solís, Juan& Méndez-Castillo, Juan José. 2014. Feature Selection for Better Identification of Subtypes of Guillain-Barré Syndrome. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016800
Modern Language Association (MLA)
Hernández-Torruco, José…[et al.]. Feature Selection for Better Identification of Subtypes of Guillain-Barré Syndrome. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1016800
American Medical Association (AMA)
Hernández-Torruco, José& Canul-Reich, Juana& Frausto-Solís, Juan& Méndez-Castillo, Juan José. Feature Selection for Better Identification of Subtypes of Guillain-Barré Syndrome. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016800
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016800