To solve the low efficiency of approximate queries caused by the large sizes of the knowledge graphs in the real world,an embedding-based approximate query method is proposed.First,the nodes in the query graph are cla...To solve the low efficiency of approximate queries caused by the large sizes of the knowledge graphs in the real world,an embedding-based approximate query method is proposed.First,the nodes in the query graph are classified according to the degrees of approximation required for different types of nodes.This classification transforms the query problem into three constraints,from which approximate information is extracted.Second,candidates are generated by calculating the similarity between embeddings.Finally,a deep neural network model is designed,incorporating a loss function based on the high-dimensional ellipsoidal diffusion distance.This model identifies the distance between nodes using their embeddings and constructs a score function.k nodes are returned as the query results.The results show that the proposed method can return both exact results and approximate matching results.On datasets DBLP(DataBase systems and Logic Programming)and FUA-S(Flight USA Airports-Sparse),this method exhibits superior performance in terms of precision and recall,returning results in 0.10 and 0.03 s,respectively.This indicates greater efficiency compared to PathSim and other comparative methods.展开更多
目的分析笔者医院2017~2021年上报的新的和严重的药品不良反应(adverse drug reactions,ADR),为临床安全合理用药、减少ADR的发生提供参考。方法对笔者医院上报的178例新的和严重的药品不良反应,进行分析总结。结果178例报告中,上报人...目的分析笔者医院2017~2021年上报的新的和严重的药品不良反应(adverse drug reactions,ADR),为临床安全合理用药、减少ADR的发生提供参考。方法对笔者医院上报的178例新的和严重的药品不良反应,进行分析总结。结果178例报告中,上报人员以药师为主(163例,91.57%);ADR主要发生在65岁以上患者(88例,49.44%);药品剂型以注射剂和片剂为主,涉及药品中抗肿瘤药物占比最高(49.82%);ADR累及损害系统/器官以血液系统最多(34.95%),其次是消化系统(29.03%)。结论临床应重视新的和严重的ADR的监测与上报,特别是抗肿瘤药物,提高药物安全性监测,保障患者的用药安全。展开更多
基金The State Grid Technology Project(No.5108202340042A-1-1-ZN).
文摘To solve the low efficiency of approximate queries caused by the large sizes of the knowledge graphs in the real world,an embedding-based approximate query method is proposed.First,the nodes in the query graph are classified according to the degrees of approximation required for different types of nodes.This classification transforms the query problem into three constraints,from which approximate information is extracted.Second,candidates are generated by calculating the similarity between embeddings.Finally,a deep neural network model is designed,incorporating a loss function based on the high-dimensional ellipsoidal diffusion distance.This model identifies the distance between nodes using their embeddings and constructs a score function.k nodes are returned as the query results.The results show that the proposed method can return both exact results and approximate matching results.On datasets DBLP(DataBase systems and Logic Programming)and FUA-S(Flight USA Airports-Sparse),this method exhibits superior performance in terms of precision and recall,returning results in 0.10 and 0.03 s,respectively.This indicates greater efficiency compared to PathSim and other comparative methods.
文摘目的分析笔者医院2017~2021年上报的新的和严重的药品不良反应(adverse drug reactions,ADR),为临床安全合理用药、减少ADR的发生提供参考。方法对笔者医院上报的178例新的和严重的药品不良反应,进行分析总结。结果178例报告中,上报人员以药师为主(163例,91.57%);ADR主要发生在65岁以上患者(88例,49.44%);药品剂型以注射剂和片剂为主,涉及药品中抗肿瘤药物占比最高(49.82%);ADR累及损害系统/器官以血液系统最多(34.95%),其次是消化系统(29.03%)。结论临床应重视新的和严重的ADR的监测与上报,特别是抗肿瘤药物,提高药物安全性监测,保障患者的用药安全。
