Ye Ye

3.3k citations
187 papers · 2.5k · h-index 25

Impact in

Papers in

Ye Ye

172 papers receiving 2.4k citations

Peers

Ye Ye
Comparison fields: 5 of 195
  • Health Informatics 47
  • Statistical and Nonlinear Physics 205
  • Infectious Diseases 220
  • Neurology 162
  • Animal Science and Zoology 109
Replace Ting Chen with:
Ting Chen China
Jiao Li China
Chun‐Houh Chen Taiwan
Chuan Lü China
Rui Jiang China
Holger Fröhlich Germany
Martin Možina Slovenia
Hua Xu United States
Hong Fang United States
James J. Chen United States
Ye Ye relative to Ting Chen China Ting Chen's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ye Ye

Since Specialization
Citations

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

Fields of papers citing papers by Ye Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 187 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007109
2 2013107
3 201397
4 200696
5 201793
6 201185
7 201574
8 202068
9 201767
10 202159
11 202153
12 202252
13 201551
14 201851
15 201848
16 201944
17 201440
18 200636
19 202135
20 201633

About Ye Ye

Ye Ye is a scholar working on Statistical and Nonlinear Physics, Epidemiology, Sociology and Political Science, Gastroenterology and Critical Care and Intensive Care Medicine, having authored 187 papers that have together received 2.5k indexed citations. Recurring topics across this work include Evolutionary Game Theory and Cooperation (24 papers), Opinion Dynamics and Social Influence (15 papers), Sepsis Diagnosis and Treatment (12 papers), Data-Driven Disease Surveillance (9 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers), Evolution and Genetic Dynamics (7 papers), Complex Systems and Time Series Analysis (7 papers) and Gastrointestinal Tumor Research and Treatment (6 papers). The work is most often cited by research in Health Informatics (47 citations), Statistical and Nonlinear Physics (205 citations), Infectious Diseases (220 citations), Neurology (162 citations) and Animal Science and Zoology (109 citations). Ye Ye has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include Nenggang Xie, Brenda G. Hogue, Chao Wang, Kang Hao Cheong, M Nekrep Perc, Attila Szolnoki, Michael M. Wagner, David J. Hak, Fuchiang Rich Tsui and Cyril P. Mauffrey. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Journal of Critical Care, The American Journal of Emergency Medicine, Surgical Endoscopy and Sustainability.

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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