Safety risks are essential to the success or failure of the large⁃scale complex projects.In order to assess and evaluate the safety risks of the large⁃scale complex projects scientifically,a risk assessment method of ...Safety risks are essential to the success or failure of the large⁃scale complex projects.In order to assess and evaluate the safety risks of the large⁃scale complex projects scientifically,a risk assessment method of work breakdown structure and risk breakdown structure(WBS⁃RBS)is proposed to identify the project risks.In this paper,interval numbers are used to evaluate the risk levels,weights are assigned automatically based on the complexity and risk degree of WBS to distinguish three types of nodes in WBS,and a risk assessment algorithm is designed to assess safety risk at all layers of the project.A case study is conducted to demonstrate how to apply the method.The results show the practicality,robustness and efficiency of our new method,which can be applied to different kinds of large⁃scale complex projects in reality.展开更多
Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an...Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an immunohistochemistry(IHC)of HER22+and requiring additional testing using fluorescence in situ hybridization to confirm the results.This paper aims to establish an automatically weighted calibration deep learning(AWCDL)algorithm to predict ERBB2 amplification based on IHC images.In this study,we applied IHC HER22+images from 1,073 breast cancer patients at three cancer centers in China and extracted 376,099 tiles.Among these,269,664 tiles were used for internal and external validation.The designed AWCDL consists of two steps.In Step 1,the internal validation achieved an accuracy of 89%,with a specificity of 0.89 and a sensitivity of 0.89.The external validation in the two other centers showed an average accuracy of 85%,with a specificity of 0.86 and a sensitivity of 0.82.In Step 2,the model achieved higher accuracy for the slides predicted as negative in Step 1 by automatically calibrating the weight.Collectively,these results suggest that this AWCDL model has successfully proved useful as an alternative method to fluorescence in situ hybridization for assessing the ERBB2 amplification status in breast cancer.展开更多
基金This paper was supported by National Social Science Foundation of China(2019⁃SKJJ⁃035)。
文摘Safety risks are essential to the success or failure of the large⁃scale complex projects.In order to assess and evaluate the safety risks of the large⁃scale complex projects scientifically,a risk assessment method of work breakdown structure and risk breakdown structure(WBS⁃RBS)is proposed to identify the project risks.In this paper,interval numbers are used to evaluate the risk levels,weights are assigned automatically based on the complexity and risk degree of WBS to distinguish three types of nodes in WBS,and a risk assessment algorithm is designed to assess safety risk at all layers of the project.A case study is conducted to demonstrate how to apply the method.The results show the practicality,robustness and efficiency of our new method,which can be applied to different kinds of large⁃scale complex projects in reality.
基金supported by the National Natural Science Foundation of China(Grant No.:81672743 and 81974464).
文摘Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an immunohistochemistry(IHC)of HER22+and requiring additional testing using fluorescence in situ hybridization to confirm the results.This paper aims to establish an automatically weighted calibration deep learning(AWCDL)algorithm to predict ERBB2 amplification based on IHC images.In this study,we applied IHC HER22+images from 1,073 breast cancer patients at three cancer centers in China and extracted 376,099 tiles.Among these,269,664 tiles were used for internal and external validation.The designed AWCDL consists of two steps.In Step 1,the internal validation achieved an accuracy of 89%,with a specificity of 0.89 and a sensitivity of 0.89.The external validation in the two other centers showed an average accuracy of 85%,with a specificity of 0.86 and a sensitivity of 0.82.In Step 2,the model achieved higher accuracy for the slides predicted as negative in Step 1 by automatically calibrating the weight.Collectively,these results suggest that this AWCDL model has successfully proved useful as an alternative method to fluorescence in situ hybridization for assessing the ERBB2 amplification status in breast cancer.
