Early Pigmentary Retinosis Diagnostic Based on Classification Trees

Autor:	Vivian Sistachs Vega, Miguel Angel Díaz Martínez, Gonzalo Joya Caparrós
Rok vydání:	2011
Předmět:	Boosting (machine learning) genetic structures business.industry Decision tree learning Speech recognition Clinical heterogeneity Optometry Dystrophy Medicine sense organs business eye diseases
Zdroj:	Advances in Computational Intelligence ISBN: 9783642215001 IWANN (1)
DOI:	10.1007/978-3-642-21501-8_41
Popis:	In this work we analyze different classification tree based techniques (CART, Bagging and Boosting), evaluating their performance with respect to their capability to reduce error rate and correct pattern classification. As a case of study we propose the classification of Pigmentary Restinosis patients through electroretinograms. Pigmentary Restinosis is the most frequent retina dystrophy (1/5000). The electroretinogram (ERG) constitutes a fundamental test in the study of this type of dystrophy since the wide clinical heterogeneity of visual diseases. Besides, retina electrophysiological study can provided information that may be used to predict the disease before the apparition of symptoms and allows us to corroborate the affectation degree on the dystrophic process of cones and canes. As experimental database we use a set of 148 electroretinograms, which is part of a retrospective study carried out by the Cuban National Reference Center of Pigmentary Retinosis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::04e33de78b5f337bd890d7c633852c9b https://doi.org/10.1007/978-3-642-21501-8_41 Zobrazit plný text záznamu