John T. Chen

570 citations
37 papers · 400 · h-index 11

Impact in

Papers in

John T. Chen

31 papers receiving 378 citations

Peers

John T. Chen
Comparison fields: 5 of 81
  • Statistics and Probability 106
  • Critical Care and Intensive Care Medicine 47
  • Internal Medicine 25
  • Statistics, Probability and Uncertainty 37
  • Biochemistry 25
Replace Gert Nielsen with:
Gert Nielsen Denmark
Bowine C. Michel Netherlands
Vincent Agboto United States
P. Roebruck Germany
Tobias Gauss France
Romin Pajouheshnia Netherlands
Farhad Arzideh Germany
Gunn B.B. Kristensen Denmark
J F McNeer United States
Jason Rho United States
John T. Chen relative to Gert Nielsen Denmark Gert Nielsen's profile →
Citations per field
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Citations per year

Countries citing papers authored by John T. Chen

Since Specialization
Citations

This map shows the geographic impact of John T. Chen'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 John T. Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Chen more than expected).

Fields of papers citing papers by John T. Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside John T. Chen, 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 John T. Chen Line = papers co-authored together John T. Chen 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 201763
2 201756
3 200444
4 201739
5 201933
6 200522
7 199321
8 201220
9 200319
10 200713
11 200410
12 20188
13 20086
14 20176
15 20146
16 20086
17 20204
18 20093
19 20183
20 20202

About John T. Chen

John T. Chen is a scholar working on Statistics and Probability, Management Science and Operations Research, Critical Care and Intensive Care Medicine, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 37 papers that have together received 400 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (8 papers), Statistical Methods and Bayesian Inference (8 papers), Statistical Methods in Clinical Trials (8 papers), Statistical Methods and Inference (7 papers), Optimal Experimental Design Methods (7 papers), Multi-Criteria Decision Making (4 papers), Trauma, Hemostasis, Coagulopathy, Resuscitation (4 papers) and Blood transfusion and management (3 papers). The work is most often cited by research in Statistics and Probability (106 citations), Critical Care and Intensive Care Medicine (47 citations), Internal Medicine (25 citations), Statistics, Probability and Uncertainty (37 citations) and Biochemistry (25 citations). John T. Chen has collaborated with scholars based in United States, Australia and Taiwan. Frequent co-authors include Roberta E. Redfern, Arjun K. Gupta, Michael G. Moront, E. Seneta, Arjun K. Gupta, C. G. Troskie, M. Eileen Walsh, Anthony J. Comerota, David L. Vogel and Burkhard Kreft. Their work appears in journals such as Journal of Statistical Computation and Simulation, Journal of ExtraCorporeal Technology, Pain Management Nursing, Journal of Pediatric Nursing and Journal of Magnetic Resonance Imaging.

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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