A combined structural-functional classification of schizophrenia using hippocampal volume plus fMRI activation
Ford, J.
Li Shen
Makedon, F.
Flashman, L.A.
Saykin, A.J.
Dept. of Comput. Sci., Dartmouth Coll., Hanover, NH, USA;
Abstract
Previous work has demonstrated that fMRI activations in individual anatomic regions can be used as a basis for classifying subjects for schizophrenia. Here we demonstrate that this classification, which is approximately 75-83% accurate for the hippocampal formation, can be improved by incorporating hippocampal volume information, which alone classifies at chance levels of accuracy. The best combined classifier is about 87% accurate and uses only right hippocampal activation and volume data. These accuracy figures should be considered approximate due to the limited size of our test dataset (N=23, 15 patients and 8 controls).
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