Clinical assessment using an algorithm based on fuzzy C-means clustering

A. Guijarro-Rodriguez; L. Cevallos-Torres; J. Yepez-Holguin; M. Botto-Tobar

doi:10.1007/978-3-319-67283-0_14

Clinical assessment using an algorithm based on fuzzy C-means clustering

A. Guijarro-Rodriguez, L. Cevallos-Torres, J. Yepez-Holguin, M. Botto-Tobar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

The Fuzzy c-means (FCM) algorithms define a grouping criterion from a function, which seeks to minimize iteratively the function up to until an optimal fuzzy partition is obtained. In the execution of this algorithm each element to the clusters is related to others that belong in the same n-dimensional space, which means that an element can belong to more than one clusters. This proposal aims to define a fuzzy clustering algorithm which allows the patient classifications based on the clinical assessment of the medical staff. In this work 30 cases were studied using the Glasgow Coma Scale to measure the level of awareness for each one which were prioritized by triage Manchester method. After applying the FCM algorithm the data is separated data into two clusters, thus, verified the fuzzy grouping in patients with a degree of membership that specifies the level of prioritization.

Original language	English
Title of host publication	Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings
Editors	Rafael Valencia-Garcia, Katty Lagos-Ortiz, Javier Del Cioppo, Nestor Vera-Lucio, Martha Bucaram-Leverone, Gema Alcaraz-Marmol
Place of Publication	Cham
Publisher	Springer
Pages	181-193
Number of pages	13
ISBN (Electronic)	978-3-319-67283-0
ISBN (Print)	978-3-319-67282-3
DOIs	https://doi.org/10.1007/978-3-319-67283-0_14
Publication status	Published - 2017
Event	3rd International Conference on Technologies and Innovation (CITI 2017) - Universidad Agraria del Ecuador, Guayaquil, Ecuador Duration: 24 Oct 2017 → 27 Oct 2017 Conference number: 3

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	749
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	3rd International Conference on Technologies and Innovation (CITI 2017)
Abbreviated title	CITI 2017
Country/Territory	Ecuador
City	Guayaquil
Period	24/10/17 → 27/10/17

Keywords

Clinical assessment
Fuzzy grouping
Fuzzy logic
Glasgow
Triage

Access to Document

10.1007/978-3-319-67283-0_14

Cite this

Guijarro-Rodriguez, A., Cevallos-Torres, L., Yepez-Holguin, J., & Botto-Tobar, M. (2017). Clinical assessment using an algorithm based on fuzzy C-means clustering. In R. Valencia-Garcia, K. Lagos-Ortiz, J. Del Cioppo, N. Vera-Lucio, M. Bucaram-Leverone, & G. Alcaraz-Marmol (Eds.), Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings (pp. 181-193). (Communications in Computer and Information Science; Vol. 749). Springer. https://doi.org/10.1007/978-3-319-67283-0_14

Guijarro-Rodriguez, A. ; Cevallos-Torres, L. ; Yepez-Holguin, J. et al. / Clinical assessment using an algorithm based on fuzzy C-means clustering. Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings. editor / Rafael Valencia-Garcia ; Katty Lagos-Ortiz ; Javier Del Cioppo ; Nestor Vera-Lucio ; Martha Bucaram-Leverone ; Gema Alcaraz-Marmol. Cham : Springer, 2017. pp. 181-193 (Communications in Computer and Information Science).

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abstract = "The Fuzzy c-means (FCM) algorithms define a grouping criterion from a function, which seeks to minimize iteratively the function up to until an optimal fuzzy partition is obtained. In the execution of this algorithm each element to the clusters is related to others that belong in the same n-dimensional space, which means that an element can belong to more than one clusters. This proposal aims to define a fuzzy clustering algorithm which allows the patient classifications based on the clinical assessment of the medical staff. In this work 30 cases were studied using the Glasgow Coma Scale to measure the level of awareness for each one which were prioritized by triage Manchester method. After applying the FCM algorithm the data is separated data into two clusters, thus, verified the fuzzy grouping in patients with a degree of membership that specifies the level of prioritization.",

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Guijarro-Rodriguez, A, Cevallos-Torres, L, Yepez-Holguin, J & Botto-Tobar, M 2017, Clinical assessment using an algorithm based on fuzzy C-means clustering. in R Valencia-Garcia, K Lagos-Ortiz, J Del Cioppo, N Vera-Lucio, M Bucaram-Leverone & G Alcaraz-Marmol (eds), Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings. Communications in Computer and Information Science, vol. 749, Springer, Cham, pp. 181-193, 3rd International Conference on Technologies and Innovation (CITI 2017), Guayaquil, Ecuador, 24/10/17. https://doi.org/10.1007/978-3-319-67283-0_14

Clinical assessment using an algorithm based on fuzzy C-means clustering. / Guijarro-Rodriguez, A.; Cevallos-Torres, L.; Yepez-Holguin, J. et al.
Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings. ed. / Rafael Valencia-Garcia; Katty Lagos-Ortiz; Javier Del Cioppo; Nestor Vera-Lucio; Martha Bucaram-Leverone; Gema Alcaraz-Marmol. Cham: Springer, 2017. p. 181-193 (Communications in Computer and Information Science; Vol. 749).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Guijarro-Rodriguez A, Cevallos-Torres L, Yepez-Holguin J, Botto-Tobar M. Clinical assessment using an algorithm based on fuzzy C-means clustering. In Valencia-Garcia R, Lagos-Ortiz K, Del Cioppo J, Vera-Lucio N, Bucaram-Leverone M, Alcaraz-Marmol G, editors, Technologies and Innovation : Third International Conference, CITI 2017, Guayaquil, Ecuador, October 24-27, 2017 : Proceedings. Cham: Springer. 2017. p. 181-193. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-67283-0_14

Clinical assessment using an algorithm based on fuzzy C-means clustering

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