Acute complication prediction model is of great importance for the overall reduction of premature death in chronic diseases.The CLSTM-BPR proposed in this paper aims to improve the accuracy,interpretability,and genera...Acute complication prediction model is of great importance for the overall reduction of premature death in chronic diseases.The CLSTM-BPR proposed in this paper aims to improve the accuracy,interpretability,and generalizability of the existing disease prediction models.Firstly,through its complex neural network structure,CLSTM-BPR considers both disease commonality and patient characteristics in the prediction process.Secondly,by splicing the time series prediction algorithm and classifier,the judgment basis is given along with the prediction results.Finally,this model introduces the pairwise algorithm Bayesian Personalized Ranking(BPR)into the medical field for the first time,and achieves a good result in the diagnosis of six acute complications.Experiments on the Medical Information Mart for Intensive Care IV(MIMIC-IV)dataset show that the average Mean Absolute Error(MAE)of biomarker value prediction of the CLSTM-BPR model is 0.26,and the average accuracy(ACC)of the CLSTM-BPR model for acute complication diagnosis is 92.5%.Comparison experiments and ablation experiments further demonstrate the reliability of CLSTM-BPR in the prediction of acute complication,which is an advancement of current disease prediction tools.展开更多
为解决计量技术机构周期巡检和日常送检设备业务量不平衡的问题,本文基于业务流程再造(Business Process Reengineering)管理思想,综合运用排队论和IDEFO过程控制图模型,根据各分流程之间的关联关系建立过程时间模型,并通过案例分析,计...为解决计量技术机构周期巡检和日常送检设备业务量不平衡的问题,本文基于业务流程再造(Business Process Reengineering)管理思想,综合运用排队论和IDEFO过程控制图模型,根据各分流程之间的关联关系建立过程时间模型,并通过案例分析,计算计量业务各分流程及全流程时间,为计量检定计划的制定提供依据。展开更多
为提高城市主干路交通流平均行程时间的估计精度,根据路段上游检测器采集的截面流量,建立了3种BPR(bureau of public roads)修正模型,包括全状态累积流量BPR修正模型、分状态标定的BPR模型和分状态累积流量BPR修正模型.仿真结果表明:全...为提高城市主干路交通流平均行程时间的估计精度,根据路段上游检测器采集的截面流量,建立了3种BPR(bureau of public roads)修正模型,包括全状态累积流量BPR修正模型、分状态标定的BPR模型和分状态累积流量BPR修正模型.仿真结果表明:全状态累积流量BPR修正模型明显优于传统的BPR模型;分状态标定的BPR模型和分状态累积流量BPR修正模型可以进一步提高估计精度,且后者可将阻滞交通状态下的平均估计误差降低至8.05%.展开更多
基金supported by the Social Science Fund of China(No.19BTQ072).
文摘Acute complication prediction model is of great importance for the overall reduction of premature death in chronic diseases.The CLSTM-BPR proposed in this paper aims to improve the accuracy,interpretability,and generalizability of the existing disease prediction models.Firstly,through its complex neural network structure,CLSTM-BPR considers both disease commonality and patient characteristics in the prediction process.Secondly,by splicing the time series prediction algorithm and classifier,the judgment basis is given along with the prediction results.Finally,this model introduces the pairwise algorithm Bayesian Personalized Ranking(BPR)into the medical field for the first time,and achieves a good result in the diagnosis of six acute complications.Experiments on the Medical Information Mart for Intensive Care IV(MIMIC-IV)dataset show that the average Mean Absolute Error(MAE)of biomarker value prediction of the CLSTM-BPR model is 0.26,and the average accuracy(ACC)of the CLSTM-BPR model for acute complication diagnosis is 92.5%.Comparison experiments and ablation experiments further demonstrate the reliability of CLSTM-BPR in the prediction of acute complication,which is an advancement of current disease prediction tools.
文摘为解决计量技术机构周期巡检和日常送检设备业务量不平衡的问题,本文基于业务流程再造(Business Process Reengineering)管理思想,综合运用排队论和IDEFO过程控制图模型,根据各分流程之间的关联关系建立过程时间模型,并通过案例分析,计算计量业务各分流程及全流程时间,为计量检定计划的制定提供依据。
文摘为提高城市主干路交通流平均行程时间的估计精度,根据路段上游检测器采集的截面流量,建立了3种BPR(bureau of public roads)修正模型,包括全状态累积流量BPR修正模型、分状态标定的BPR模型和分状态累积流量BPR修正模型.仿真结果表明:全状态累积流量BPR修正模型明显优于传统的BPR模型;分状态标定的BPR模型和分状态累积流量BPR修正模型可以进一步提高估计精度,且后者可将阻滞交通状态下的平均估计误差降低至8.05%.
