Machine Learning to Predict Interim Response in Pediatric Classical Hodgkin Lymphoma Using Affordable Blood Tests

Keyphrases

• Pediatric 100%
• Blood Test 100%
• Machine Learning 100%
• Classical Hodgkin Lymphoma 100%
• Interim Response 100%
• Early Response 80%
• Positron Emission Tomography/computerized Tomography 80%
• Deauville Score 60%
• Pediatric Patients 40%
• Albumin 40%
• Lactate Dehydrogenase 40%
• Ferritin 40%
• Erythrocyte Sedimentation Rate 40%
• Absolute Lymphocyte Count 40%
• White Cell Count 40%
• South African 20%
• African Countries 20%
• Standard of Care 20%
• Radiotherapy 20%
• Hemoglobin 20%
• Blood Samples 20%
• Logistic Regression 20%
• K-nearest 20%
• Test Accuracy 20%
• Predictive Variables 20%
• Undertreatment 20%
• Doxorubicin 20%
• Receiver Operating Characteristic 20%
• Interim Analysis 20%
• Blood Test Results 20%
• Python 20%
• Prediction Accuracy 20%
• Vinblastine 20%
• Bleomycin 20%
• Dacarbazine 20%
• Response Assessment 20%
• Regression Forest 20%
• Support Vector Machine Classifier 20%
• Chemosensitivity 20%
• Random Forest Analysis 20%
• 2-cycles 20%
• Scikit-learn 20%
• Difference Variables 20%
• Absolute Eosinophil Count 20%
• Nave Bayes 20%
• Single Difference 20%

Medicine and Dentistry

• Pediatrics 100%
• Classical Hodgkin Lymphoma 100%
• Computer Assisted Tomography 80%
• Positron Emission Tomography 80%
• Ferritin 40%
• Pediatrics Patient 40%
• Cell Count 40%
• Leukocyte 40%
• Lymphocyte 40%
• Erythrocyte Sedimentation Rate 40%
• Lactate Dehydrogenase 40%
• Health Care Cost 20%
• Clinical Finding 20%
• Logistic Regression Analysis 20%
• Doxorubicin 20%
• Dacarbazine 20%
• Vinblastine 20%
• Bleomycin 20%
• Chemosensitivity 20%
• Interim Analysis 20%
• Eosinophil 20%
• Radiation Therapy 20%

Immunology and Microbiology

• Albumin 50%
• Random Forest 50%
• K Nearest Neighbor 25%
• Support Vector Machine 25%
• Pythonidae 25%
• Eosinophil Count 25%
• Chemosensitivity 25%
• Hemoglobin 25%