Machine Learning Models in Prediction of Treatment Response After Chemoembolization with MRI Clinicoradiomics Features

Keyphrases

• Chemoembolization 100%
• Contrast Enhancement 100%
• Machine Learning Models 100%
• Treatment Response Prediction 100%
• Radiomics 80%
• T1WI 80%
• Clinical Features 60%
• Local Response 60%
• Data Combination 60%
• Feature Selection Methods 40%
• Feature Selection 40%
• Support Vector Machine Model 40%
• Sequential Feature Selection 40%
• Phase Contrast 20%
• Neutrophils 20%
• Treatment Response 20%
• Non-responders 20%
• MRI Images 20%
• Data Augmentation 20%
• Clinical Information 20%
• Performance Metrics 20%
• Nave 20%
• Area under the Curve 20%
• Pearson Correlation Coefficient 20%
• Laboratory Data 20%
• Intraclass Correlation Coefficient 20%
• Model Performance 20%
• T1-MRI 20%
• European Association for the Study of the Liver 20%
• Procedural Information 20%
• Arterial Phase 20%
• MRI Radiomics 20%

Biochemistry, Genetics and Molecular Biology

• Magnetic Resonance Imaging 100%
• Radiomics 100%
• Feature Extraction 100%
• Support Vector Machine 50%
• Retrospective Study 25%
• Leukocyte 25%

Neuroscience

• Magnetic Resonance Imaging 100%
• Support Vector Machine 66%
• Leukocyte 33%