Objective: To determine the associated factors for in-hospital mortality in patients with meningeal cryptococcosis and HIV infection at a local hospital in Lima, Perú. Materials and methods: We carried out a case...Objective: To determine the associated factors for in-hospital mortality in patients with meningeal cryptococcosis and HIV infection at a local hospital in Lima, Perú. Materials and methods: We carried out a case-control study by reviewing the medical histories available at a local hospital in Lima, Peru. We determined the factors associated with mortality using a logistic regression model. Results: The information of 90 patients was analyzed, 37 dead and 53 alive. In the multivariate analysis we found two variables associated with mortality: Glasgow at admission (OR = 4.55 (1.61 – 12.20), p = 0.01) and serum antigen titer greater than 1024 (OR = 20.48 (1.6 – 261.04, p = 0.02). The protective factor found was a longer hospitalization stay (OR = 0.80 (0.69 – 0.93, p = 0.005).Conclusions: A low Glasgow score and serum antigen titer greater than 1024 are associated factors with mortality, whereas hospitalization length is a protective factor.展开更多
This paper addresses the development of a random forest classifier for the muki-class fault diagnosis in spur gearboxes. The vibration signal＇s condition parameters are first extracted by applying the wavelet packet ...This paper addresses the development of a random forest classifier for the muki-class fault diagnosis in spur gearboxes. The vibration signal＇s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients＇ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters＇ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.展开更多
文摘Objective: To determine the associated factors for in-hospital mortality in patients with meningeal cryptococcosis and HIV infection at a local hospital in Lima, Perú. Materials and methods: We carried out a case-control study by reviewing the medical histories available at a local hospital in Lima, Peru. We determined the factors associated with mortality using a logistic regression model. Results: The information of 90 patients was analyzed, 37 dead and 53 alive. In the multivariate analysis we found two variables associated with mortality: Glasgow at admission (OR = 4.55 (1.61 – 12.20), p = 0.01) and serum antigen titer greater than 1024 (OR = 20.48 (1.6 – 261.04, p = 0.02). The protective factor found was a longer hospitalization stay (OR = 0.80 (0.69 – 0.93, p = 0.005).Conclusions: A low Glasgow score and serum antigen titer greater than 1024 are associated factors with mortality, whereas hospitalization length is a protective factor.
文摘This paper addresses the development of a random forest classifier for the muki-class fault diagnosis in spur gearboxes. The vibration signal＇s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients＇ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters＇ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.
