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Big Data in Radiation Oncology gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. While basic principles and key analytical and processing techniques are introduced in the early chapters, the rest of the book turns to clinical applications, in particular for cancer registries, informatics, radiomics, radiogenomics, patient safety and quality of care, patient-reported outcomes, comparative effectiveness, treatment planning, and clinical decision-making.
Features of Big Data in Radiation Oncology PDF:
- Offers the first focused treatment of the role of big data in the clinic and its impact on radiation therapy.
- Covers applications in cancer registry, radiomics, patient safety, quality of care, treatment planning, decision making, and other key areas.
- Discusses the fundamental principles and techniques for processing and analysis of big data.
- Address the use of big data in cancer prevention, detection, prognosis, and management.
- Provides practical guidance on implementation for clinicians and other stakeholders.
About the Author:
Jun Deng, PhD, is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an American Board of Radiology board-certified medical physicist at Yale New Haven Hospital.
Lei Xing, PhD, is currently the Jacob Haimson Professor of Medical Physics and Director of the Medical Physics Division of the Radiation Oncology Department of Stanford University.
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