An analysis on cure time of patients with COVID-19 / 西安交通大学学报(医学版)

【Objective】 To analyze the cure time from diagnosis to cure of coronavirus disease 2019(COVID-19). 【Methods】 Based on the time of admission, diagnosis, and discharge of cured cases announced by the provincial and municipal health committees, the average period from diagnosis to discharge was calculated. And based on the aggregate data including the cumulative number of diagnoses, the number of curedcases and the number of deaths and their proportional relationship, we calculated the cure time. 【Results】 The cure time curve of 580 COVID-19 patients had skewed distribution, with a skewness of 1.09, a mean cure time of (14.6±6.7) days, a median of 13 days, and a 95% confidence interval (6.9, 21.0). The average cure time calculated based on the relationship between the cumulative number of diagnoses, the number of cured cases and the number of deaths was (13.3±3.5)d, with a median of 13.5 d. The average value of the cure time calculated based on the proportion of cured cases to the number of endpoints was (14.2±4.2)d, with the median number of 14.5 d. Based on the calculation of the relationship between the cumulative number of diagnosed cases, the number of cured cases and the number of deaths, the median cure time of cases with COVID-19 in Wuhan, Hubei Province, and the whole country was 15 days, 15.5 days and 15 days, respectively. The mediancure time for COVID-19cases in Wuhan, Hubei, and the whole country was 14 days. 【Conclusion】 The median cure time of COVID-19 is 13-15.5 days. There is some variation at different time of the outbreak, but there is not much difference between different regions.

Study on classification and identification of depressed patients and healthy people among adolescents based on optimization of brain characteristics of network / 生物医学工程学杂志

To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (