Mi Mu

3.1k citations
10 papers · 2.0k indexed · 2 hit papers · h-index 8

Impact in

    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research
  • Neurology top 1%
    • Long-Term Effects of COVID-19

Papers in

Mi Mu

10 papers receiving 1.9k citations

Hit Papers

Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan. A Retrospective Observational Study 2020 · 642 citations
64220202026202220244008001.2k

Peers

Mi Mu
Comparison fields: 5 of 112
  • Infectious Diseases 1.4k
  • Neurology 762
  • Critical Care and Intensive Care Medicine 102
  • Applied Microbiology and Biotechnology 31
  • Oncology 339
Replace Yingzhen Du with:
Yingzhen Du China
Pengcheng Yang China
Qinyong Hu China
Bohan Yang China
Yongxi Zhang China
Pingzheng Mo China
Shihui Song China
Liping Deng China
Mingqi Luo China
Mi Mu relative to Yingzhen Du China Yingzhen Du's profile →
Citations per field
00.5×1.5×
Yingzhen Du · 1×
Citations per year

Countries citing papers authored by Mi Mu

Since Specialization
Citations

This map shows the geographic impact of Mi Mu'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 Mi Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mi Mu more than expected).

Fields of papers citing papers by Mi Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mi Mu. 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 Mi Mu. The network helps show where Mi Mu may publish in the future.

Co-authors

The 25 scholars most cited alongside Mi Mu, 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 Mi Mu Line = papers co-authored together Mi Mu links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Clinical Characteristics of COVID-19 Patients With Digestive Symptoms in Hubei, China: A Descriptive, Cross-Sectional, Multicenter Study
Hit paper breakdown →
20201234
2
Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan. A Retrospective Observational Study
Hit paper breakdown →
2020642
3 202033
4 202117
5 202114
6 202112
7 20247
8 20217
9 20216
10 20221

About Mi Mu

Mi Mu is a scholar working on Immunology and Allergy, Infectious Diseases, Neurology, Pulmonary and Respiratory Medicine and Dermatology, having authored 10 papers that have together received 2.0k indexed citations. Recurring topics across this work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), COVID-19 Clinical Research Studies (3 papers), Long-Term Effects of COVID-19 (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Lung Cancer Diagnosis and Treatment (1 paper), IL-33, ST2, and ILC Pathways (1 paper), Pleural and Pulmonary Diseases (1 paper) and Dermatology and Skin Diseases (1 paper). The work is most often cited by research in Infectious Diseases (1.4k citations), Neurology (762 citations), Critical Care and Intensive Care Medicine (102 citations), Applied Microbiology and Biotechnology (31 citations) and Oncology (339 citations). Mi Mu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Guogang Xu, Yingzhen Du, Tianzhi Li, Qinyong Hu, Runsheng Wang, Chao Hu, Pengcheng Yang, Lei Tu, Jun‐Hong Yan and Lei Pan. Their work appears in journals such as Cancer Management and Research, Journal of Autoimmunity, Frontiers in Immunology, Frontiers in Medicine and Hypertension.

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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2026