Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16)

  • Zelinka I
ISSN: 03603016
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Abstract

Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried??out effectively in a few normal tissue complication probability studies and should become a common strategy. ?? 2010 Elsevier Inc. All rights reserved.

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APA

Zelinka, I. (2016). Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16), 451, 41–48. Retrieved from http://link.springer.com/10.1007/978-3-319-33609-1%0Ahttp://link.springer.com/10.1007/978-3-319-33816-3

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