Study populations of included studies. by Martha R. Smith (20410184)

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Future research directions. by Martha R. Smith (20410184)

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PRISMA flow diagram. by Martha R. Smith (20410184)

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S9 File - by Martha R. Smith (20410184)

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S7 File - by Martha R. Smith (20410184)

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Participant characteristics of included studies. by Martha R. Smith (20410184)

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Signals detection based on sex and subgroup at the SOC level utilizing two disproportionality analysis methods. by Mengsi Peng (12882734)

Forest Plot of the incidence of adverse events in the MSCs therapy group and control group. by Luz Estella Mesa (8339283)

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Wage gaps by gender, sector and year. by Mingming Li (502877)

“…<div><p>Although the Chinese government has implemented a variety of measures, the gender wage gap in 21^st century China has not decreased. …”

Enrichment of known events in DILI before adverse histopathology based on gene sets as well as individual gene members. by Anika Liu (8411805)

“…Only for peroxisomal pathways, both directions were significantly enriched indicating that dysregulation in direction might be linked to adverse histopathology.…”

Adversely interacting drug pairs and non-interacting drug pairs significantly differ with regard to the 11 features selected. by Sheng Qian (5944997)

Forest Plot of the incidence of serious adverse events in MSCs therapy group and control group. by Luz Estella Mesa (8339283)

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L’Abbé plot for the incidence of adverse events in the MSCs therapy group and control group. by Luz Estella Mesa (8339283)

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Table 2_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.docx by Yiqu Wei (22011386)

Image 4_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image 1_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image 3_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Table 1_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.docx by Yiqu Wei (22011386)

Image 2_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

The funnel plot based on COVID-19 infection in non-health care workers (A) and health care workers (B). by Zhuoyang Xia (21354186)