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[IC‐P‐137]: ADNI‐3 MRI PROTOCOL
Author(s) -
Gunter Jeffrey L.,
Borowski Bret J.,
Thostenson Kaely,
Arani Arvin,
Reid Robert I.,
Cash David M.,
Thomas David L.,
Zhang Hui,
DeCarli Charles S.,
Fox Nick C.,
Thompson Paul M.,
Tosun Duygu,
Weiner Michael,
Jack Clifford R.
Publication year - 2017
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.2017.06.2411
Subject(s) - fluid attenuated inversion recovery , diffusion mri , computer science , neuroimaging , scanner , protocol (science) , artificial intelligence , nuclear medicine , magnetic resonance imaging , neuroscience , medicine , radiology , psychology , pathology , alternative medicine
(fMRI, sMRI and fMRI+sMRI) at each stages (LC: low-confidence, Base: base classifier, HC: high-confidence). Panel B show, on top, the average maps for each modality and on the bottom the subtype maps used for the high-confidence prediction. Panel C show the coefficients of the high-confidence prediction model for each subtype map. Panel D show the contribution of each modality to the decision, the ratio are computed by the sum of the absolute coefficient for each modality.