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<p>A multi-model fusion evaluation method based on indexes construction is discussed in this paper for evaluating the maturity level of an Uncertainty Analysis System for Radiotherapy (UASR). First, a system for evaluating the capability maturity of the UASR is established. Second, three first-level evaluation indicators for people, technology and process are constructed, and twelve second-level evaluation indicators are formed under the three first-level indicators. Next, by combining the Analytic Hierarchy Process (AHP) with the Entropy Weight Method (EWM), the subjectivity brought by the AHP is reduced, and the AHP-EWM model is combined with a Fuzzy Synthetic Evaluation Model (FSEM). The level of the maturity model is determined by both scoring mechanisms together, making the assessment more reliable than that produced when a single model is used. To assess the maturity of the target hospital, UASR maturity assessment software is designed, and the affiliated hospital of the University of South China is selected for a practical application. After the experts’ scores are input into the UASR maturity assessment software, the calculated final score of 0.7848 confirms that the UASR reaches the management level, indicating a robust management framework and enhanced operational capacity. This research offers a practical methodology for optimizing the implementation of the UASR and guiding its iterative improvement.</p>

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A methodological design and an empirical study for assessing the maturity of an UASR based on the AHP-EWM and the FSEM fusion model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Chong Guo,
  • Bing Tang

摘要

A multi-model fusion evaluation method based on indexes construction is discussed in this paper for evaluating the maturity level of an Uncertainty Analysis System for Radiotherapy (UASR). First, a system for evaluating the capability maturity of the UASR is established. Second, three first-level evaluation indicators for people, technology and process are constructed, and twelve second-level evaluation indicators are formed under the three first-level indicators. Next, by combining the Analytic Hierarchy Process (AHP) with the Entropy Weight Method (EWM), the subjectivity brought by the AHP is reduced, and the AHP-EWM model is combined with a Fuzzy Synthetic Evaluation Model (FSEM). The level of the maturity model is determined by both scoring mechanisms together, making the assessment more reliable than that produced when a single model is used. To assess the maturity of the target hospital, UASR maturity assessment software is designed, and the affiliated hospital of the University of South China is selected for a practical application. After the experts’ scores are input into the UASR maturity assessment software, the calculated final score of 0.7848 confirms that the UASR reaches the management level, indicating a robust management framework and enhanced operational capacity. This research offers a practical methodology for optimizing the implementation of the UASR and guiding its iterative improvement.