BioDash: A semantic web dashboard for drug development
Eric K. Neumann, Dennis Quan
PSB 2006
This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease. © 2012 SPIE.
Eric K. Neumann, Dennis Quan
PSB 2006
Wesam Alramadeen, Yu Ding, et al.
IISE Transactions on Healthcare Systems Engineering
Irina Rish, Gerald Tesauro
IM 2007
Andreana Gomez, Sergio Gonzalez, et al.
Toxics