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- 저자 : Furukawa Kyoji (검색결과 1 건)
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SUMRAY: R and Python Codes for Calculating Cancer Risk Due to Radiation Exposure of a Population
Sasaki Michiya,Furukawa Kyoji,Satoh Daiki,Shimada Kazumasa,Kudo Shin’ichi,Takagi Shunji,Takahara Shogo,Kai Michiaki 대한방사선방어학회 2023 방사선방어학회지 Vol.48 No.2
Background : Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations . In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into ac- count uncertainties . We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection . Materials and Methods : SUMRAY has two versions of code written in R and Python . The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki . The confidence intervals associated with the evaluated risks were derived by propagating the statisti- cal uncertainties in the risk model parameter estimates by the Monte Carlo method . JRPR Results and Discussion : SUMRAY was used to calculate the lifetime or time-integrated attrib- utable risks of cancer under an exposure scenario (baseline rates , dose[s] , age[s] at exposure , age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool , Radiation Risk Assessment Tool (Rad- RAT; National Institutes of Health) , and showed a reasonable agreement within the estimated confidential interval . Compared with RadRAT, SUMRAY can be used for a wide range of ap- plications , as it allows the risk projection with arbitrarily specified risk models and/or popula- tion reference data . Conclusion : The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes . The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license .
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