Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.
Mark DrakesmithKaren CaeyenberghsA. DuttG. LewisA. S. DavidDerek K. JonesPublished in: NeuroImage (2015)
Keyphrases
- false positives
- data sets
- data analysis
- data points
- database
- data collection
- false positive rate
- raw data
- data structure
- high dimensional
- object recognition
- synthetic data
- high quality
- graph representation
- probability distribution
- knowledge discovery
- recognition rate
- input data
- high dimensional data
- missing data
- spatial data
- training data