A two-layer nested heterogeneous ensemble learning predictive method for COVID-19 mortality.

The COVID-19 epidemic has had a great adverse impact on the world, having taken a heavy toll, killing hundreds of thousands of people. In order to help the world better combat COVID-19 and reduce its death toll, this study focuses on the COVID-19 mortality. First, using the multiple stepwise regression analysis method, the factors from eight aspects (economy, society, climate etc.) that may affect the mortality rates of COVID-19 in various countries is examined. In addition, a two-layer nested heterogeneous ensemble learning-based prediction method that combines linear regression (LR), support vector machine (SVM), and extreme learning machine (ELM) is developed to predict the development trends of COVID-19 mortality in various countries. Based on data from 79 countries, the experiment proves that age structure (proportion of the population over 70 years old) and medical resources (number of beds) are the main factors affecting the mortality of COVID-19 in each country. In addition, it is found that the number of nucleic acid tests and climatic factors are correlated with COVID-19 mortality. At the same time, when predicting COVID-19 mortality, the proposed heterogeneous ensemble learning-based prediction method shows better prediction ability than state-of-the-art machine learning methods such as LR, SVM, ELM, random forest (RF), long short-term memory (LSTM) etc.

[Effects of Eupolyphaga Sinensis Walker on erythrocyte's CR1 activity and anti-cardiolipin antibody level in rats with stagnation of blood].

AIM: To study the effect of Eupolyphaga Sinensis Walker(ESW) on red blood cell immune adherence (RCIA) and serum anticardiolipin antibody level in rat model of Yin-deficiency Huo-excess with chronic blood stasis. METHODS: The model was made by i.m. injection of dexamethasone (0.5 mg/kg) and adrenaline (0.84 mg/kg). The serum anti-cardiolipin antibodies (ACA) ACA-IgG, ACA-IgA and ACA-IgM and the plasma D-dimmer levels were measured by using enzyme-linked immunosorbent assay (ELISA). The body and organ weight of the rats were measured. RESULTS: For rats of Yin-deficiency Huo-excess, rosette rates of red blood cell C3b receptors (RBC-C3b RR) and red blood cell cancer (RBC-CaR) decreased, the serum ACA-IgG, ACA-IgA, ACA-IgM and the plasma D-dimmer levels markedly increased, body weight and the weight of spleen and thymus all decreased. ESW (5 mg/kg, 10 mg/kg) increased RBC-C3bRR and RBC-CaR, reduced serum ACA-IgG, ACA-IgA, ACA-IgM and plasma D-dimmer levels, and increased spleen weight of the rats. CONCLUSION: ESW can boost the immune function in rats of Yin-deficiency Huo-excess with chronic blood stasis.