Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status.
Carole H. SudreJasmina PanovskaEser SanverdiSebastian BrandnerVasileios K. KatsarosGeorge StranjalisFrancesca B. PizziniClaudio GhimentonKatarina Surlan-PopovicJernej AvsenikMaria Vittoria SpampinatoMario NigroArindam R. ChatterjeeArnaud AttyeSylvie GrandAlexandre KrainikNicoletta AnzaloneGian Marco ConteValeria RomeoLorenzo UggaAndrea ElefanteElisa Francesca CiceriElia GuadagnoEftychia E. KapsalakiDiana RöttgerJavier GonzalezTimothé BoutelierM. Jorge CardosoSotirios BisdasPublished in: BMC Medical Informatics Decis. Mak. (2020)
Keyphrases
- machine learning
- low grade
- pattern recognition
- decision trees
- machine learning methods
- text classification
- support vector machine
- supervised machine learning
- supervised learning
- image classification
- genetic algorithm
- machine learning approaches
- machine learning algorithms
- magnetic resonance imaging
- computer vision
- feature selection
- supervised classification
- data mining
- classification algorithm
- classification accuracy
- medical images
- model selection
- unsupervised learning
- text mining
- genetic algorithm ga
- multi class
- magnetic resonance images
- support vector
- feature extraction
- breast cancer
- differential evolution
- feature vectors
- data analysis
- neural network