A Guide to Outcome Modeling In Radiotherapy and Oncology (Series in Medical Physics and Biomedical Engineering)
目次
Section I: Multiple sources of data Chapter 1: Introduction to data sources and outcome models Chapter 2: Cinical data in outcome models Chapter 3: Imaging data: Radiomics Chapter 4: Dosimetric data Chapter 5: Pre-Clinical Radiobiological insights to inform modelling of radiotherapy outcome Chapter 6: Biological data: The use of omics in outcome models Section II: Top-down Modeling Approaches Chapter 7: Analytical and mechanistic modeling Chapter 8: Data driven approaches I: using conventional statistical inference methods, including linear and logistic regression Chapter 9: Data driven approaches II: Machine Learning Section III: Bottom-up Modeling Approaches Chapter 10: Stochastic multiscale modelling of biological effects induced by ionizing radiation Chapter 11: Multiscale modeling approaches: Application in Chemo and immunotherapies Section IV: Example Applications in Oncology Chapter 12: Outcome Modeling in Treatment Planning Chapter 13: A Utility Based Approach to Individualized and Adaptive Radiation Therapy Chapter 14: Outcome modeling in Particle therapy Chapter 15: Modeling response to oncological surgery Chapter 16: Tools for the precision medicine era: Developing highly adaptive and personalized treatment recommendations using SMARTs
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