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Classification model based on strain measurements to identify patients with arrhythmogenic cardiomyopathy with left ventricular involvement.

Fecha de publicación: Fecha Ahead of Print:

Autores de IIS La Fe

Participantes ajenos a IIS La Fe

  • Vives-Gilabert Y
  • Sanz-Sánchez J
  • Calvillo-Batllés P
  • Castells F

Grupos

Abstract

A heterogenous expression characterizes arrhythmogenic cardiomyopathy (AC). The evaluation of regional wall movement included in the current Task Force Criteria is only qualitative and restricted to the right ventricle. However, a strain-based approach could precisely quantify myocardial deformation in both ventricles. We aim to define and modelize the strain behavior of the left ventricle in AC patients with left ventricular (LV) involvement by applying algorithms such as Principal Component Analysis (PCA), clustering and naïve Bayes (NB) classifiers.

Datos de la publicación

ISSN/ISSNe:
0169-2607, 1872-7565

Computer Methods and Programs in Biomedicine  ELSEVIER IRELAND LTD

Tipo:
Article
Páginas:
105296-105296
PubMed:
31918194
Factor de Impacto:
0,924 SCImago ℠
Cuartil:
Q1 SCImago ℠

Citas Recibidas en Web of Science: 3

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Keywords

  • Cardiac magnetic resonance imaging, Clustering, Naïve Bayes classification

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