Mahalanobis-Taguchi analysis of the significance of data about canceroous tumors in the breast
DOI:
https://doi.org/10.61117/ipsumtec.v6i1.175Keywords:
Mahalanobis distance, SNR, Orthogonal arrays, Correlation matrixAbstract
In this work, the Mahalanobis-Taguchi System (MTS) was applied to database on breast cancer at the Hospital of the University of Wisconsin, located in Madison, which oversees Dr. William H. Wolberg. The Mahalanobis methodology measures the distances in multivariable systems, considering correlation between the variables analyzed. On the other hand, this system is also applied to make predictions through a multivariate measurement scale. The purpose of this study is to determine the significant variables to identify the differences from one group to another, and thus calculate the Mahalanobis distance (DT) between two groups of patients: the first, with cancerous tumors (unhealthy group), and the second. second group diagnosed as healthy.
Downloads
Metrics
References
G. Taguchi, "Taguchi methods in LSI fabrication process," 2001 6th International Workshop on Statistical Methodology (Cat. No.01TH8550), 2001, pp. 1-6, doi: 10.1109/IWSTM.2001.933815. DOI: https://doi.org/10.1109/IWSTM.2001.933815
Hong, J., Cudney, E. A., Taguchi, G., Jugulum, R., Paryani, K., & Ragsdell, K.M. (2005, January). A comparison study of Mahalanobis-Taguchi system and neural network for multivariate pattern recognition. In ASME International Mechanical Engineering Congress and Exposition (Vol.42150, pp. 109-115). DOI: https://doi.org/10.1115/IMECE2005-80029
N.N.N.M. Kamil, S.N.A.M. Zainiand M.Y. Abu (2020), A case study on the application of Mahalanobis-Taguchi system for magnetic component, INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGY AND SCIENCES (IJETS) ISSN: 2289-697X (Print); ISSN:2462-1269 (Online) Vol.7(2) December 2020© Universiti Malaysia Pahang DOI: http://dx.doi.org/10.15282/ijets.7.2.2020.1001
W.Z.A.W. Muhamad, F. Ramlieand K.R. Jamaludin. (2017), Mahalanobis-Taguchi System For Pattern Recognition: A Brief Review, Far East Journal of Mathematical Sciences (FJMS) Pushpa Publishing House, Allahabad, India http://www.pphmj.comhttp://dx.doi.org/10.17654/MS10212302 Volume102,Number12,2017,Pages3021-3052 ISSN:0972-0871 DOI: https://doi.org/10.17654/MS102123021
William H Woodall, Rachelle Koudelik, Kwok-Leung Tsui, Seoung Bum Kim, Zachary G Stoumbos & Christos P Carvounis MD (2003) A Review and Analysis of the Mahalanobis—Taguchi System, Technometrics, 45:1, 1-15, DOI: 10.1198/004017002188618626 DOI: https://doi.org/10.1198/004017002188618626
Xiao, X., Fu, D., Shi, Y., & Wen, J. (2020). Optimized Mahalanobis–Taguchi System for High-Dimensional Small Sample Data Classification. Computational Intelligence and Neuroscience, 2020.
José Manuel Pizarro León, Rey David Molina Arredondo, Roberto Romero López, Oscar Nuñez Ortega (2015), Análisis de robustez de procesos para evaluar factibilidad de implementar control en línea, CULCYT.
Medina V., Pedro Daniel; Cruz T., Eduardo Arturo; Hernan Restrepo, Jorge (2007), Aplicación del modelo de experimentación Taguchi en un ingenio azucarero del Valle del Cauca Scientia Et Technica, vol. XIII, núm.34, pp. 337-342
Genichi Taguchi, Rajesh Jugulum (2002), The Mahalanobis-Taguchi Strategy: A Pattern Technology System, 1st Edition, John Wiley & Sons DOI: https://doi.org/10.1002/9780470172247
Jorge Limón, Manuel A. Rodriguez, Yolanda A. Báez y Diego A. Tlapa (2011), Evaluación de la Robustez del sistema Mahalanobis–Taguchi a diferentes Arreglos Factoriales, Revista Información Tecnológica DOI: https://doi.org/10.4067/S0718-07642011000400010
M. Rodríguez M., M.I. Rodríguez B., Luz I. Rodríguez A., J. L. López G., (2015), Determinación de los factores influyentes sobre los índices de reprobación y eficiencia terminal mediante la Metodología Mahalanobis-Taguchi en una Institución de Educación Superior (IES), Theorema-Revista Científica, UTCJ.
Xinping Xiao, Dian Fu, Yu Shi,Jianghui Wen, "Optimized Mahalanobis–Taguchi System for High-Dimensional Small Sample Data Classification", Computational Intelligence and Neuroscience, vol. 2020, Article ID4609423, 15 pages, 2020. https://doi.org/10.1155/2020/4609423 DOI: https://doi.org/10.1155/2020/4609423
Mota-Gutiérrez, C.G., Reséndiz-Flores, E.O. and Reyes-Carlos, Y.I. (2018), "Mahalanobis-Taguchi system: state of the art", International Journal of Quality & Reliability Management, Vol. 35 No. 3, pp. 596-613. https://doi.org/10.1108/IJQRM-10-2016-0174 DOI: https://doi.org/10.1108/IJQRM-10-2016-0174
Ghasemi, E., Aaghaie, A. and Cudney, E.A. (2015),"Mahalanobis Taguchi system: a review", International Journal of Quality & Reliability Management, Vol. 32No. 3, pp. 291-307. https://doi.org/10.1108/IJQRM-02-2014-0024 DOI: https://doi.org/10.1108/IJQRM-02-2014-0024
Su, C. T. (2017). Mahalanobis-Taguchi system and its medical applications. Neuropsychiatry, 7(4), 316-320.
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Manuel Arnoldo Rodríguez Medina , Manuel Iván Rodríguez Borbón , Jorge Adolfo Pinto Santos , Ericka Berenice Herrera Ríos , Inocente Yuliana Meléndez Pastrana

This work is licensed under a Creative Commons Attribution 4.0 International License.
