Neuronanatomy, neurology and Bayesian networks


Autoria(s): Bielza Lozoya, Maria Concepcion
Data(s)

2014

Resumo

Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related quality of life in Parkinson's disease. Most of these challenging problems posed by neuroscience involve new Bayesian network designs that can cope with multiple class variables, small sample sizes, or labels annotated by several experts.

Formato

application/pdf

Identificador

http://oa.upm.es/36279/

Idioma(s)

eng

Publicador

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

Relação

http://oa.upm.es/36279/1/INVE_MEM_2014_172469.pdf

Direitos

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

info:eu-repo/semantics/openAccess

Fonte

| 8th European Conference on Data Mining (DM2014) | 15-17 Jul 2014 | Lisboa

Palavras-Chave #Matemáticas
Tipo

info:eu-repo/semantics/conferenceObject

Ponencia en Congreso o Jornada

PeerReviewed