Patrick Ten Eyck

96 papers receiving 2.1k citations

Patrick Ten Eyck's Hit Papers

Sex-Based Differences in Susceptibility to Severe Acute Respiratory Syndrome Coronavirus Infection 2017 · 637 citations
6370+3+6Years since publication200400600

Peers

Patrick Ten Eyck
Comparison fields: 5 of 130
  • Infectious Diseases 768
  • Obstetrics and Gynecology 169
  • Modeling and Simulation 86
  • Neurology 134
  • Internal Medicine 52
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Countries citing papers authored by Patrick Ten Eyck

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Ten Eyck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Sex-Based Differences in Susceptibility to Severe Acute Respiratory Syndrome Coronavirus Infection
Hit paper breakdown →
2017637
2 2017234
3 2021106
4 2018103
5 202073
6 201861
7 202150
8 202148
9 202044
10 202342
11 202334
12 202033
13 201724
14 201924
15 202021
16 202121
17 202119
18 202318
19 202218
20 202018

About Patrick Ten Eyck

Patrick Ten Eyck is a scholar working on Neurology, Pathology and Forensic Medicine, Nephrology, Infectious Diseases and Cardiology and Cardiovascular Medicine, having authored 114 papers that have together received 2.1k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (8 papers), Assisted Reproductive Technology and Twin Pregnancy (4 papers), COVID-19 Clinical Research Studies (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Transcranial Magnetic Stimulation Studies (4 papers), Airway Management and Intubation Techniques (3 papers), COVID-19 and Mental Health (3 papers) and Clinical Reasoning and Diagnostic Skills (3 papers). The work is most often cited by research in Infectious Diseases (768 citations), Obstetrics and Gynecology (169 citations), Modeling and Simulation (86 citations), Neurology (134 citations) and Internal Medicine (52 citations). Patrick Ten Eyck has collaborated with scholars based in United States, Saudi Arabia and France. Frequent co-authors include Stanley M. Perlman, David Kyle Meyerholz, Rudragouda Channappanavar, Craig Fett, Matthias Mack, Chaorong Wu, Abeer N. Alshukairi, Nicholas T. Trapp, Laila Ali Layqah and Yunshu Zhou. Their work appears in journals such as PLoS ONE, Fertility and Sterility, Annals of Emergency Medicine, American Journal of Respiratory and Critical Care Medicine and Brain stimulation.

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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