A novel approach to malignant-benign classification of pulmonary nodules by using ensemble learning classifiers.
Ahmet TartarAydin AkanNiyazi KilicPublished in: EMBC (2014)
Keyphrases
- ensemble learning
- benign and malignant
- pulmonary nodules
- thoracic ct images
- ensemble classifier
- breast cancer
- generalization ability
- multiple classifiers
- individual classifiers
- digital mammograms
- lung nodules
- weak learners
- computer aided
- ct images
- support vector
- ensemble methods
- computer aided diagnosis
- feature selection
- breast tissue
- ct scans
- random forest
- classification models
- pattern recognition
- malignant melanoma
- dce mri
- support vector machine
- classification algorithm
- base classifiers
- classification accuracy
- concept drift
- lung cancer
- training set
- feature extraction
- training data
- feature space
- training samples
- support vector machine svm
- class labels
- training examples
- image processing
- machine learning
- decision trees
- data streams
- medical domain
- roc curve
- data mining
- svm classifier
- machine learning algorithms