A combined structural-functional classification of schizophrenia using hippocampal volume plus fMRI activation

James Ford, Li Shen, Fillia Makedon, Laura A. Flashman, Andrew J. Saykin

Research output: Contribution to journalConference article

10 Scopus citations

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).

Original languageEnglish (US)
Pages (from-to)48-49
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - Dec 1 2002
Externally publishedYes
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

Keywords

  • Classification
  • FLD
  • Schizophrenia

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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