Manyun Li

25 papers receiving 355 citations

Manyun Li's Hit Papers

The prevalence and risk factors of mental problems in medical students during COVID-19 pandemic: A systematic review and meta-analysis 2022 · 140 citations
1400+1+2Years since publication4080120

Peers

Manyun Li
Comparison fields: 5 of 76
  • Clinical Psychology 86
  • Biological Psychiatry 9
  • General Health Professions 73
  • Experimental and Cognitive Psychology 31
  • Nephrology 16
Replace N. A. Uvais with:
N. A. Uvais India
Emily P. Morris United States
Ryan L. Brown United States
Jean‐Pierre Schuster France
Michio Hosaka Japan
Heidi Combs United States
Israel Krieger Israel
Saba Asif Pakistan
Bo Wei China
Andreas Birkhofer Germany
Manyun Li relative to N. A. Uvais India N. A. Uvais's profile →
Citations per field
00.5×3.5×
N. A. Uvais · 1×
Citations per year

Countries citing papers authored by Manyun Li

Since Specialization
Citations

This map shows the geographic impact of Manyun Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Manyun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manyun Li more than expected).

Fields of papers citing papers by Manyun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Manyun Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Manyun Li. The network helps show where Manyun Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Manyun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Manyun Li Line = papers co-authored together Manyun Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The prevalence and risk factors of mental problems in medical students during COVID-19 pandemic: A systematic review and meta-analysis
Hit paper breakdown →
2022140
2 202138
3 202318
4 202118
5 202215
6 202115
7 202314
8 202312
9 202011
10 202410
11 20218
12 20228
13 20237
14 20236
15 20236
16 20226
17 20226
18 20246
19 20235
20 20233

About Manyun Li

Manyun Li is a scholar working on Clinical Psychology, Cognitive Neuroscience, Experimental and Cognitive Psychology, Molecular Biology and Pharmacology, having authored 26 papers that have together received 359 indexed citations. Recurring topics across this work include Mental Health Research Topics (3 papers), Functional Brain Connectivity Studies (3 papers), Stress Responses and Cortisol (2 papers), Thyroid Disorders and Treatments (2 papers), COVID-19 and Mental Health (2 papers), Inflammasome and immune disorders (2 papers), Diet and metabolism studies (1 paper) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Clinical Psychology (86 citations), Biological Psychiatry (9 citations), General Health Professions (73 citations), Experimental and Cognitive Psychology (31 citations) and Nephrology (16 citations). Manyun Li has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Tieqiao Liu, Qiuxia Wu, Yueheng Liu, Yuejiao Ma, Shubao Chen, Yuzhu Hao, Pu Peng, Qianjin Wang, Yingying Wang and Xin Wang. Their work appears in journals such as Annals of Medicine, Frontiers in Public Health, Journal of Affective Disorders, Frontiers in Psychiatry and European Archives of Psychiatry and Clinical Neuroscience.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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