Big Data in Radiation Oncology

Series Preface

Preface

Acknowledgments

Editors

Contributors

1. Big data in radiation oncology: Opportunities and challenges

Jean-Emmanuel Bibault

2. Data standardization and informatics in radiation oncology

Charles S. Mayo

3. Storage and databases for big data

Tomas Skripcak, Uwe Just, Ida Schoenfeld, Esther G.C. Troost, and Mechthild Krause

4. Machine learning for radiation oncology

Yi Luo and Issam El Naqa

5. Cloud computing for big data

Sepideh Almasi and Guillem Pratx

6. Big data statistical methods for radiation oncology

Yu Jiang, Vojtech Huser, and Shuangge Ma

7. From model-driven to knowledge- and data-based treatment planning

Morteza Mardani, Yong Yang, Yinyi Ye, Stephen Boyd, and Lei Xing

8. Using big data to improve safety and quality in radiation oncology

Eric Ford, Alan Kalet, and Mark Phillips

9. Tracking organ doses for patient safety in radiation therapy

Wazir Muhammad, Ying Liang, Gregory R. Hart, Bradley J. Nartowt, David A. Roffman, and Jun Deng

10. Big data and comparative effectiveness research in radiation oncology

Sunil W. Dutta, Daniel M. Trifiletti, and Timothy N. Showalter

11. Cancer registry and big data exchange

Zhenwei Shi, Leonard Wee, and Andre Dekker

12. Clinical and cultural challenges of big data in radiation oncology

Brandon Dyer, Shyam Rao, Yi Rong, Chris Sherman, Mildred Cho, Cort Buchholz, and Stanley Benedict

13. Radiogenomics

Barry S. Rosenstein, Gaurav Pandey, Corey W. Speers, Jung Hun Oh, Catharine M.L. West, and Charles S. Mayo

14. Radiomics and quantitative imaging

Dennis Mackin and Laurence E. Court

15. Radiotherapy outcomes modeling in the big data era

Joseph O. Deasy, Aditya P. Apte, Maria Thor, Jeho Jeong, Aditi Iyer, Jung Hun Oh, and Andrew Jackson

16. Multi-parameterized models for early cancer detection and prevention

Gregory R. Hart, David A. Roffman, Ying Liang, Bradley J. Nartowt, Wazir Muhammad, and Jun Deng

Index

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• Tecnologia, engenharia, agricultura
• Física médica
• Oncologia
• Engenharia biomédica

Roc;Image Guided Radiation Therapy;IGRT;Clinical Informatics;Radiation Oncology;Learning Health Care Systems;Data Sets;Radiation Oncology Process;Normal Tissue Complication Probability Model;High Dimensional Measurements;Clinical Practice;Random Forest;Dose Distribution;Patient Reported Outcomes;DVH Curve;Big Data System;DVH;Big Data;Normal Tissue Toxicity;BN Structure Learning;Roc Curve;MC Dose Calculation;MC Dose;Inverse Planning;Organ Doses