The pooled effect of all-cause mortality rate in non-health care workers and health care workers. حسب Zhuoyang Xia (21354186)

Cochrane Collaboration’s risk of bias tool. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Grade system. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Literature search. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Study characteristics. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Flowchart of literature retrieval. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Data extraction. حسب Zhuoyang Xia (21354186)

"…Regarding COVID-19 severity, no significant difference were found for asymptomatic (pooled RR 1.18; 95%CI: 0.81–1.72), mild to moderate (pooled RR 0.99; 95%CI: 0.84–1.17), severe COVID-19 (pooled RR 1.25; 95%CI: 0.92–1.70), hospitalization (pooled RR 0.93; 95%CI: 0.58–1.50) or all-cause mortality (pooled RR 0.60; 95%CI: 0.18–1.95) between BCG and placebo groups. …"

Descriptive statistics of variables. حسب Yanling Li (269030)

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Matched kernel density function diagram. حسب Yanling Li (269030)

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Matching estimation results of propensity score. حسب Yanling Li (269030)

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Sample balance test. حسب Yanling Li (269030)

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Robustness test results. حسب Yanling Li (269030)

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Heterogeneity test at different educational levels. حسب Yanling Li (269030)

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Results of baseline regression. حسب Yanling Li (269030)

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Unmatched kernel density function diagram. حسب Yanling Li (269030)

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Risk of bias. حسب Da Huang (1306407)

"…Normally presenting with symptoms such as dyspnea, decreased exercise tolerance, decreased maximal heart rate, and decreased arterial oxygen saturation. …"

Overall risk of bias assessment. حسب Da Huang (1306407)

"…Normally presenting with symptoms such as dyspnea, decreased exercise tolerance, decreased maximal heart rate, and decreased arterial oxygen saturation. …"

Sampling scenarios used in our experiments. حسب Anna Beatriz Silva (20989245)

"…<div><p>Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. …"

Hybridsampling triple size models performance. حسب Anna Beatriz Silva (20989245)

"…<div><p>Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. …"

PCA-CGAN model parameter settings. حسب Chao Tang (10925)

"…Simultaneously, we designed a two-stage conditional encoding-decoding architecture that builds category-independent feature spaces from early training stages, fundamentally breaking the feature space bias caused by the “Matthew effect” and effectively preventing majority classes from compressing minority class features during generation. …"