Mingkai Peng

1.0k citations
35 papers · 696 · h-index 15

Impact in

Papers in

Mingkai Peng

34 papers receiving 683 citations

Peers

Mingkai Peng
Comparison fields: 5 of 113
  • Cardiology and Cardiovascular Medicine 285
  • Health Information Management 53
  • Pulmonary and Respiratory Medicine 204
  • Epidemiology 119
  • Geriatrics and Gerontology 13
Replace Francesco Cozzolino with:
Francesco Cozzolino Italy
Gary Globe United States
Toshihiko Takada Japan
Dominique Monlezun United States
Chengyin Ye China
Yanbo Zhang China
Jack W. O’Sullivan United Kingdom
Lukas Staub Switzerland
Mikhail Dziadzko France
Ayan Sen United States
Mingkai Peng relative to Francesco Cozzolino Italy Francesco Cozzolino's profile →
Citations per field
00.5×2.5×
Francesco Cozzolino · 1×
Citations per year

Countries citing papers authored by Mingkai Peng

Since Specialization
Citations

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

Fields of papers citing papers by Mingkai Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017141
2 201998
3 201849
4 201643
5 201233
6 201531
7 201930
8 201827
9 201727
10 201826
11 201924
12 201823
13 201818
14 201817
15 201816
16 201714
17 202010
18 20178
19 20158
20 20178

About Mingkai Peng

Mingkai Peng is a scholar working on Cardiology and Cardiovascular Medicine, Health Information Management, Pulmonary and Respiratory Medicine, Information Systems and Epidemiology, having authored 35 papers that have together received 696 indexed citations. Recurring topics across this work include Blood Pressure and Hypertension Studies (6 papers), Medical Coding and Health Information (5 papers), Cardiovascular Function and Risk Factors (4 papers), Data Mining Algorithms and Applications (4 papers), Health Promotion and Cardiovascular Prevention (3 papers), Forest ecology and management (3 papers), Tree Root and Stability Studies (3 papers) and Emergency and Acute Care Studies (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (285 citations), Health Information Management (53 citations), Pulmonary and Respiratory Medicine (204 citations), Epidemiology (119 citations) and Geriatrics and Gerontology (13 citations). Mingkai Peng has collaborated with scholars based in Canada, Australia and Switzerland. Frequent co-authors include Hude Quan, Tyler Williamson, Guanmin Chen, Cathy A. Eastwood, Chelsea Doktorchik, Danielle A. Southern, Mitja Jevnikar, Marc Humbert, Jason Weatherald and Gérald Simonneau. Their work appears in journals such as International Journal for Population Data Science, PLoS ONE, Canadian Journal of Forest Research, The Stata Journal Promoting communications on statistics and Stata and JAMA Network Open.

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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