Generating reference models for structurally complex data: application to the stabilometry medical domain

Alonso Amo, Fernando ORCID: https://orcid.org/0000-0001-9437-9258, Lara Torralbo, Juan Alfonso, Martínez Normand, Loïc ORCID: https://orcid.org/0000-0002-6906-5828, Pérez Pérez, Aurora ORCID: https://orcid.org/0000-0001-6495-3474 and Caraça-Valente Hernández, Juan Pedro (2013). Generating reference models for structurally complex data: application to the stabilometry medical domain. "Methods of Information in Medicine", v. 52 (n. 5); pp. 441-453. ISSN 0026-1270. https://doi.org/10.3414/ME12-01-0106.

Descripción

Título: Generating reference models for structurally complex data: application to the stabilometry medical domain
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Methods of Information in Medicine
Fecha: 2013
ISSN: 0026-1270
Volumen: 52
Número: 5
Materias:
ODS:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

We present a framework specially designed to deal with structurally complex data, where all individuals have the same structure, as is the case in many medical domains. A structurally complex individual may be composed of any type of singlevalued or multivalued attributes, including time series, for example. These attributes are structured according to domain-dependent hierarchies. Our aim is to generate reference models of population groups. These models represent the population archetype and are very useful for supporting such important tasks as diagnosis, detecting fraud, analyzing patient evolution, identifying control groups, etc.

Más información

ID de Registro: 26397
Identificador DC: https://oa.upm.es/26397/
Identificador OAI: oai:oa.upm.es:26397
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/571330
Identificador DOI: 10.3414/ME12-01-0106
URL Oficial: http://www.schattauer.de/en/magazine/subject-areas...
Depositado por: Memoria Investigacion
Depositado el: 21 Jul 2014 09:34
Ultima Modificación: 12 Nov 2025 00:00