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The Role of Big Data in Radiation Oncology: Challenges and Potentials

The Role of Big Data in Radiation Oncology: Challenges and Potentials

Issam El Naqa
Copyright: © 2016 |Pages: 24
ISBN13: 9781466698406|ISBN10: 1466698403|EISBN13: 9781466698413
DOI: 10.4018/978-1-4666-9840-6.ch069
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MLA

El Naqa, Issam. "The Role of Big Data in Radiation Oncology: Challenges and Potentials." Big Data: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 1519-1542. https://doi.org/10.4018/978-1-4666-9840-6.ch069

APA

El Naqa, I. (2016). The Role of Big Data in Radiation Oncology: Challenges and Potentials. In I. Management Association (Ed.), Big Data: Concepts, Methodologies, Tools, and Applications (pp. 1519-1542). IGI Global. https://doi.org/10.4018/978-1-4666-9840-6.ch069

Chicago

El Naqa, Issam. "The Role of Big Data in Radiation Oncology: Challenges and Potentials." In Big Data: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1519-1542. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9840-6.ch069

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Abstract

More than half of cancer patients receive ionizing radiation as part of their treatment and it is the main modality at advanced stages of disease. Treatment outcomes in radiotherapy are determined by complex interactions between cancer genetics, treatment regimens, and patient-related variables. A typical radiotherapy treatment scenario can generate a large pool of data, “Big data,” that is comprised of patient demographics, dosimetry, imaging features, and biological markers. Radiotherapy data constitutes a unique interface between physical and biological data interactions. In this chapter, the authors review recent advances and discuss current challenges to interrogate big data in radiotherapy using top-bottom and bottom-top approaches. They describe the specific nature of big data in radiotherapy and discuss issues related to bioinformatics tools for data aggregation, sharing, and confidentiality. The authors also highlight the potential opportunities in this field for big data research from bioinformaticians as well as clinical decision-makers' perspectives.

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