Predicting dementia development in Parkinson's disease using Bayesian network classifiers

Psychiatry Research - Neuroimaging

Volumn 213, Issue 2, 2013, Pages 92-98

  Morales, Dinora A ^a   Vives Gilabert, Yolanda ^b,c   Gómez Ansón, Beatriz ^d   Bengoetxea, Endika ^e   Larrañaga, Pedro ^a   Bielza, Concha ^a   Pagonabarraga, Javier ^d   Kulisevsky, Jaime ^d   Corcuera Solano, Idoia ^d   Delfino, Manuel ^b,c  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b Port d'Informació Científica ^*  (Spain)

^c UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

^d HOSPITAL DE LA SANTA CREU I SANT PAU   (Spain)

^e UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

Feature selection; Freesurfer segmentation; Machine learning methods; MCI; MRI; Neuroimaging

Indexed keywords

AGED; ARTICLE; BAYES THEOREM; BRAIN CORTEX; BRAIN REGION; BRAIN SIZE; BRAIN VENTRICLE; CLINICAL ARTICLE; COGNITION; DEMENTIA; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE CLASSIFICATION; FEMALE; HUMAN; MALE; MILD COGNITIVE IMPAIRMENT; MINI MENTAL STATE EXAMINATION; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PARKINSON DISEASE; PREDICTIVE VALUE; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; UNIFIED PARKINSON DISEASE RATING SCALE;

AGED; BAYES THEOREM; BRAIN; DEMENTIA; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; PARKINSON DISEASE; PREDICTIVE VALUE OF TESTS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINES;

EID: 84879460078     PISSN: 09254927     EISSN: 18727506     Source Type: Journal    
DOI: 10.1016/j.pscychresns.2012.06.001     Document Type: Article

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