MedVir: an interactive representation system of multidimensional medical data applied to Traumatic Brain Injury's rehabilitation prediction


Autoria(s): González Tortosa, Santiago; Gracia Berna, Antonio; Herrero Martín, María del Pilar; Perales Castellanos, Nazareth; Paul Lapedriza, Nuria
Data(s)

2014

Resumo

Clinicians could model the brain injury of a patient through his brain activity. However, how this model is defined and how it changes when the patient is recovering are questions yet unanswered. In this paper, the use of MedVir framework is proposed with the aim of answering these questions. Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.

Formato

application/pdf

Identificador

http://oa.upm.es/37580/

Idioma(s)

eng

Publicador

E.T.S. de Ingenieros Informáticos (UPM)

Relação

http://oa.upm.es/37580/1/37580_INVE_MEM_2014_197012.pdf

http://link.springer.com/chapter/10.1007%2F978-3-319-08729-0_24

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

Rough sets and intelligent systems paradigms | Second International Conference on Rough Sets and Intelligent Systems Paradigms | 9-13 Jul 2014 | Madrid y Granada

Palavras-Chave #Medicina #Informática
Tipo

info:eu-repo/semantics/conferenceObject

Ponencia en Congreso o Jornada

PeerReviewed