Early Diagnosis of Mild Cognitive Impairment Using Random Forest Feature Selection.
Parisa ForouzannezhadAlireza AbbaspourMercedes CabrerizoMalek AdjouadiPublished in: BioCAS (2018)
Keyphrases
- random forest
- early diagnosis
- mild cognitive impairment
- feature set
- feature selection
- computer aided
- fold cross validation
- early stage
- high degree of accuracy
- computer aided diagnosis
- decision trees
- text categorization
- early detection
- data preparation
- brain images
- multi label
- ensemble methods
- feature extraction
- classification accuracy
- feature subset
- clinical trials
- prostate cancer
- machine learning
- naive bayes
- text classification
- support vector
- multi class
- image analysis
- preprocessing
- base classifiers
- knowledge discovery