1.Analysis of No.12b Lymph Node Dissection for 60 Cases of Advanced Distal Gastric Cancer Accepting D_2 Lymphadenectomy
Chinese Journal of Bases and Clinics in General Surgery 2003;0(05):-
Objective To study the necessity and feasibility of No.12b lymph node dissection in D2 lymphadenectomy for advanced distal gastric cancer,and the relation between No.12b lymph node metastasis and clinicopathologic factors.Methods Clinical data of sixty cases of advanced distal gastric cancer receiving D2 or D2+ radical correction were collected retrospectively,both of which were all plus No.12b lymph node dissections.The relationships between No.12b lymph node metastasis and clinicopathologic factors were analyzed.Results No death attributed to operation or severe operative complications were found.There were 12 cases(20.00%) with No.12b lymph node metastasis.The rates of No.12b lymph node metastasis in Borrmann Ⅲ-Ⅳ types,N2-3 of lymph node metastasis and T3-4 of tumor infiltration were 31.25%(10/32),30.30%(10/33) and 29.73%(11/37),which were significantly higher than those in Borrmann Ⅰ-Ⅱ types(7.14%(2/28)),N0-1(7.41%(2/27)) and T1-2(4.35%(1/23)) respectively(P
2.Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm
Chinese Journal of Medical Physics 2024;41(6):788-792
A novel data detection algorithm is proposed to improve the data detection efficiency of the operation and maintenance management system for the hospital microservices platform.Based on the multiple characteristics of the platform data,the algorithm constructs the overall framework of the operation and maintenance management system.By combining the parameter optimization ability of genetic algorithm and the rapid detection ability of LightGBM algorithm,the effective detection of the flow data in the operation and maintenance management system is realized.The effectiveness of the model is verified through a control test,and the results show that the proposed method performs the best in intelligent flow detection,achieving accuracy of 0.981 0,recall rate of 0.68 and F1 value of 0.77 which are all higher than those of the traditional methods.