الملخص
Abstract@#Survival analysis has been widely used in the field of medical research. The Cox proportional hazard model is commonly used, but its practical application is limited. Machine learning method can compensate for the shortcomings of the Cox proportional hazard model in terms of nonlinear data processing and prediction accuracy. This article reviewed the advance of machine learning methods represented by neural networks, within the field of survival analysis, and highlighted the principles and benefits of three machine learning methods that DeepSurv, Deep-Hit and random survival forest, providing methodological insights for the analysis of complex survival data.
الملخص
Abstract In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began to break out in the Hubei Province of China. At present, the epidemic situation in the world continues and the number of confirmed cases is increasing every day. A recent review showed that children under the age of ten years make up about 1% of the infected population, which cannot be ignored. Studies have shown that after SARS-CoV-2 infection children can show clinical symptoms of cardiovascular system damage in addition to typical respiratory symptoms. This article mainly discusses the possible damage of SARS-CoV-2 to children's cardiovascular system and related mechanisms.