Vision 20/20: Automation and advanced computing in clinical radiation oncology
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States)
- Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 26504 (Greece)
- Department of Radiation Oncology and Molecular Radiation Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231 (United States)
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri 63110 (United States)
This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.
- OSTI ID:
- 22251215
- Journal Information:
- Medical Physics, Vol. 41, Issue 1; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-2405
- Country of Publication:
- United States
- Language:
- English
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