Chinese Named Entity Recognition of Epidemiological Investigation of Information on COVID-19 Based on BERT

The named entity recognition based on the epidemiological investigation of information on COVID-19 can help analyze the source and route of transmission of the epidemic to control the spread of the epidemic better. Therefore, this paper proposes a Chinese named entity recognition model BERT-BiLSTM-IDCNN-ELU-CRF (BBIEC) based on the epidemiological investigation of information on COVID-19 of the BERT pre-training model. The model first processes the unlabeled epidemiological investigation of information on COVID-19 into the character-level corpus and annotates it with artificial entities according to the BIOES character-level labeling system and then uses the BERT pre-training model to obtain the word vector with position information;then, through the bidirectional long-short term memory neural network (BiLSTM) and the improved iterated dilated convolutional neural network (IDCNN) extract global context and local features from the generated word vectors and concatenate them serially;output all possible label sequences to the conditional random field (CRF);finally pass the condition random The airport decodes and generates the entity tag sequence. The experimental results show that the model is better than other traditional models in recognizing the entity of the epidemiological investigation of information on COVID-19.

Expressions of SAA, CRP, and FERR in different severities of COVID-19.

OBJECTIVE: To explore the expression and significance of SAA, CRP and FERR in patients diagnosed with COVID-19. PATIENTS AND METHODS: A total of 225 patients diagnosed with COVID-19 who were admitted to the North Hospital of First Hospital in Changsha, China, from 9th February 2020 to 7th March 2020 were enrolled. Their general data, laboratory test results and levels of SAA, CRP and FERR were extracted from electronic medical records. RESULTS: Age was an important risk factor for the severity of COVID-19 in the patients. Compared with the non-severe group, the severe group showed statistical significance in the levels of total protein, albumin, ALT and AST in liver function, UA in renal function, myocardial enzyme CK-MB and LDH, and immunoglobulin IgG and IgM. The levels of SAA, CRP, and FERR were significantly increased in patients with severe COVID-19. ROC curve analysis results showed that the AUC, from small to large, was as follows: SAA+CRP+FERR, CRP + FERR, SAA + CRP, SAA + FERR, SAA, FERR, and CRP, which indicated the benefit of the combination of the three indicators. The sensitivity and specificity of the combined detection of the three indicators were higher than those of the detection of any single indicator or two combined indicators. A Spearman correlation analysis of the data showed that the initial CRP/SAA, SAA/FERR, and CRP/FERR were positively correlated. The continuous results of SAA, CRP and FERR throughout the study period showed that the values of the severe group on a given day were higher than those of the non-severe group; the values of the two groups peaked on the 5th or 7th day and then decreased, and the decreasing trend of the severe group was more evident. CONCLUSIONS: SAA, CRP and FERR are sensitive serological indicators used to evaluate the severity of COVID-19. The combined detection of serum SAA, FERR, and CRP, which are positively related to COVID-19 infection, offers guiding significance for the occurrence of COVID-19 infection and the severity of the disease. Such detection provides effective detection indicators for the progress and prognosis of COVID-19; these indicators will enable effective intervention measures to be implemented in time and the rates of severe illness and mortality to be reduced.

Coronavirus disease 2019: a clinical review.

In December 2019, an outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported in Wuhan, China, and it subsequently spread in many countries around the world. Many efforts have been applied to control and prevent the spread of COVID-19, and many scientific studies have been conducted in a short period of time. Here we present an overview of the viral structure, pathogenesis, diagnosis, and clinical features of COVID-19 based on the current state of knowledge, and we compare its clinical characteristics with SARS and Middle East Respiratory Syndrome (MERS). Current researches on potentially effective treatment alternatives are discussed. We hope this review can help medical workers and researchers around the world contain the current COVID-19 pandemic.