Effect of sample size on multi-parametric prediction of tissue outcome in acute ischemic stroke using a random forest classifier.
Nils Daniel ForkertJens FiehlerPublished in: Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging (2015)
Keyphrases
- sample size
- ischemic stroke
- random sampling
- small sample size
- upper bound
- model selection
- covariance matrix
- statistical power
- small sample
- pac learning
- number of training samples
- statistical tests
- confidence intervals
- worst case
- experimental design
- vc dimension
- prediction model
- small samples
- data mining
- progressive sampling
- face recognition
- dimensionality reduction
- decision making
- statistical hypothesis testing
- image registration
- random sample
- variance reduction
- health care
- image analysis
- evolutionary computation