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IC‐P‐178: Multimodal support vector machine for automated detection of functional and structural disconnection in Alzheimer's disease
Author(s) -
Dyrba Martin,
Grothe Michel,
Kirste Thomas,
Teipel Stefan
Publication year - 2013
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2013.05.175
Subject(s) - diffusion mri , support vector machine , disconnection , pattern recognition (psychology) , functional connectivity , artificial intelligence , computer science , resting state fmri , correlation , tractography , white matter , neuroscience , psychology , medicine , mathematics , magnetic resonance imaging , geometry , political science , law , radiology
lobes or the preand post-central gyri. Based on these results, a summary ROI composed of the frontal and temporal lobes but excluding the sensory/motor areas was generated which obtains complete separation between the two groups. Figure 1 shows a boxplot of stiffness. Conclusions: It has been previously reported that global brain stiffness is decreased in subjects with AD [1]. We now report a specific pattern of fronto-temporal stiffness reduction in FTD, expanding the diagnostic utility of this novel biomarker of neurodegenerative disease.References: [1] Murphy et al. JMRI 2011. 34(3): 494.