Ling Chen

1.9k citations
103 papers · 1.3k · h-index 19

Impact in

Papers in

    • Statistical Methods and Inference 13
    • Statistical Methods and Bayesian Inference 12
    • Advanced Statistical Methods and Models 6
    • Statistical Distribution Estimation and Applications 4
    • Statistical Methods in Clinical Trials 4

Ling Chen

90 papers receiving 1.2k citations

Peers

Ling Chen
Comparison fields: 5 of 148
  • Otorhinolaryngology 48
  • Statistics and Probability 102
  • Pathology and Forensic Medicine 148
  • Surgery 289
  • Orthopedics and Sports Medicine 50
Replace Douglas Landsittel with:
Douglas Landsittel United States
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Citations per field
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Citations per year

Countries citing papers authored by Ling Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ling Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012212
2 2019104
3 201171
4 201568
5 199566
6 201061
7 201445
8 201340
9 202031
10 202030
11 201829
12 201924
13 202023
14 201922
15 202021
16 200921
17
Nurses' Stress Associated with Nursing Activities and Electronic Health Records: Data Triangulation from Continuous Stress Monitoring, Perceived Workload, and a Time Motion Study.
201921
18 202019
19 202119
20 201718

About Ling Chen

Ling Chen is a scholar working on Statistics and Probability, Oncology, Pathology and Forensic Medicine, Public Health, Environmental and Occupational Health and Artificial Intelligence, having authored 103 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Statistical Methods and Bayesian Inference (12 papers), Bayesian Methods and Mixture Models (6 papers), Advanced Statistical Methods and Models (6 papers), Endoplasmic Reticulum Stress and Disease (5 papers), Statistical Distribution Estimation and Applications (4 papers), Diabetic Foot Ulcer Assessment and Management (4 papers) and Statistical Methods in Clinical Trials (4 papers). The work is most often cited by research in Otorhinolaryngology (48 citations), Statistics and Probability (102 citations), Pathology and Forensic Medicine (148 citations), Surgery (289 citations) and Orthopedics and Sports Medicine (50 citations). Ling Chen has collaborated with scholars based in United States, China and South Africa. Frequent co-authors include Nathan A. Mall, Rick W. Wright, Corey S. Gill, Robert H. Brophy, Matthew J. Matava, Matthew V. Smith, Jianguo Sun, Tamara Hershey, Anjum Hassan and Friederike Kreisel. Their work appears in journals such as Journal of Clinical Oncology, Computational Statistics & Data Analysis, Journal of the American Statistical Association, American Journal of Clinical Pathology and Clinical Biomechanics.

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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