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Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

IEEE

Author: Pous i Sabadí, Carles
Caballero, Dani
López Ibáñez, Beatriz
Abstract: This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage
Document access: http://hdl.handle.net/2072/66802
Language: eng
Publisher: IEEE
Rights: Tots els drets reservats
Subject: Anàlisi multivariable
Diagnòstic -- Informàtica
Raonament basat en casos
Medicina -- Informàtica
Case-based reasoning
Diagnosis -- Data processing
Medicine -- Data processing
Multivariate analysis
Title: Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning
Type: info:eu-repo/semantics/article
Repository: Recercat

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