Personalized Risk Prediction in Clinical Oncology Research: Applications and Practical Issues Using Survival Trees and Random Forests

Mathematics

• Random Forest 100%
• Oncology 96%
• Classification and Regression Trees 67%
• Prediction 54%
• Prediction Model 52%
• Recursive Partitioning 43%
• High-dimensional 22%
• Multimodality 20%
• Tree Algorithms 19%
• Missing Covariates 18%
• Model Specification 18%
• Pruning 17%
• Breast Cancer 17%
• Parameter Tuning 16%
• Progression 15%
• Tumor 14%
• Censoring 14%
• Clinical Trials 13%
• Recurrence 13%
• Predict 12%
• Scenarios 12%
• Model-based 12%
• Monte Carlo Simulation 11%
• Covariates 11%
• Regression Model 11%
• Evaluate 10%
• Costs 10%
• Interaction 9%
• Higher Order 9%
• Simulation Study 9%
• Relationships 8%
• Demonstrate 8%
• Model 4%

Medicine & Life Sciences

• Forests 81%
• Medical Oncology 81%
• Phase III Clinical Trials 16%
• Survival 15%
• Genetic Markers 14%
• Progression-Free Survival 12%
• Randomized Controlled Trials 9%
• Demography 8%
• Breast Neoplasms 8%
• Costs and Cost Analysis 8%
• Recurrence 7%
• Therapeutics 6%
• Neoplasms 4%