Skip to content

Latest commit

 

History

History
2 lines (2 loc) · 389 Bytes

README.md

File metadata and controls

2 lines (2 loc) · 389 Bytes

Classifying Glioblastoma Progression According to RANO Criteria with Deep Learning and Radiomics-Based Random Forest ©

Hybrid Convolutional Neural Network and Random Forest Model to Predict Glioblastoma RANO Progression Response. The Random Forest model takes a radiomics approach, extracting relevant quantitative features from tumour regions and predicting RANO response accordingly.