Reference : Computer Aided Diagnosis System Based on Random Forests for the Prognosis of Alzheime...
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/222467
Computer Aided Diagnosis System Based on Random Forests for the Prognosis of Alzheimer’s Disease
English
Wehenkel, Marie mailto [Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Bastin, Christine mailto [Université de Liège - ULiège > Département des sciences cliniques > Neuroimagerie des troubles de la mémoire et révalid. cogn. >]
Geurts, Pierre mailto [Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Algorith. des syst. en interaction avec le monde physique >]
Phillips, Christophe mailto [Université de Liège - ULiège > > Centre de recherches du cyclotron >]
Apr-2018
1st HBP Student Conference - Transdisciplinary Research Linking Neuroscience, Brain Medicine and Computer Science
Frontiers Media S.A.
Yes
International
978-2-88945-421-1
1st Human Brain Project Student Conference
from 08-02-2017 to 10-02-2017
Human Brain Project
Vienna
Austria
[en] Random Forests ; CAD ; Alzheimer's disease
[en] In this abstract, we propose an original CAD system consisting in the combination of
brain parcelling, ensemble of trees methods, and selection of (groups of) features using
the importance scores embedded in tree-based methods. Indeed, on top of their ease
of use and accuracy without ad hoc parameter tuning, tree ensemble methods such as
random forests (RF) (Breiman, 2001) or extremely randomized trees (ET) (Geurts et
al., 2006) provide interpretable results in the form of feature importance scores. We also
compare the performance and interpretability of our proposed method to standard RF
and ET approaches, without feature selection, and to multiple kernel learning (MKL). The latter was shown to be an efficient method notably capable of
dealing with anatomically defined regions of the brain by the use of multiple kernels.
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/222467
10.3389/978-2-88945-421-1

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