Mingchen Song

26 papers receiving 1.4k citations

Peers

Mingchen Song
Comparison fields: 5 of 106
  • Nephrology 342
  • Critical Care and Intensive Care Medicine 211
  • Immunology 169
  • Epidemiology 235
  • Biological Psychiatry 16
Replace Matijs van Meurs with:
Matijs van Meurs Netherlands
Sang‐Kyung Jo South Korea
Eizo Watanabe Japan
Benjamin G. Chousterman France
Osamu Takasu Japan
Christophe Lelubre Belgium
Shaltiel Cabili Israel
Dietmar Krausch Germany
Jessica A. Dominguez United States
Yanfen Chai China
Mingchen Song relative to Matijs van Meurs Netherlands Matijs van Meurs's profile →
Citations per field
00.5×1.5×
Matijs van Meurs · 1×
Citations per year

Countries citing papers authored by Mingchen Song

Since Specialization
Citations

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

Fields of papers citing papers by Mingchen Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004195
2 2006167
3 2004158
4 2004152
5 2005142
6 2004135
7 2004119
8 200290
9 200468
10 200641
11 200031
12 201630
13 200828
14 200028
15 201419
16 201514
17 200410
18 201110
19 20077
20 20023

About Mingchen Song

Mingchen Song is a scholar working on Pulmonary and Respiratory Medicine, Epidemiology, Immunology, Molecular Biology and Nephrology, having authored 37 papers that have together received 1.5k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (6 papers), Immune Response and Inflammation (6 papers), Respiratory Support and Mechanisms (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Renal function and acid-base balance (3 papers), Cardiac Arrhythmias and Treatments (2 papers), Venous Thromboembolism Diagnosis and Management (2 papers) and Advanced Drug Delivery Systems (2 papers). The work is most often cited by research in Nephrology (342 citations), Critical Care and Intensive Care Medicine (211 citations), Immunology (169 citations), Epidemiology (235 citations) and Biological Psychiatry (16 citations). Mingchen Song has collaborated with scholars based in United States, Vietnam and South Korea. Frequent co-authors include John A. Kellum, Jinyou Li, Ramesh Venkataraman, Mitchell P. Fink, Eyad Almasri, David S. Phelps, Ramesh Venkataraman, Robert L. Albright, Vincent J. Capponi and James F. Winchester. Their work appears in journals such as CHEST Journal, Critical Care Medicine, Blood Purification, Journal of Pharmacology and Experimental Therapeutics and American Journal of Therapeutics.

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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