Kevin M. Hellman

43 papers receiving 927 citations

Peers

Kevin M. Hellman
Comparison fields: 5 of 87
  • Endocrine and Autonomic Systems 143
  • Reproductive Medicine 117
  • Cognitive Neuroscience 256
  • Public Health, Environmental and Occupational Health 311
  • Behavioral Neuroscience 37
Replace Zhi Yi Ong with:
Zhi Yi Ong Australia
Angie M. Cason United States
Zivjena Vucetic United States
T.C.D. Burazin Australia
Kenneth G. Onishi United States
A. Larcher France
Silvia Begliuomini Italy
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Citations per year

Countries citing papers authored by Kevin M. Hellman

Since Specialization
Citations

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

Fields of papers citing papers by Kevin M. Hellman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017141
2 200495
3 200391
4 201352
5 200747
6 200644
7 202133
8 201028
9 201328
10 199828
11 202027
12 201526
13 201826
14 201223
15 200623
16 201720
17 201117
18 201917
19 201616
20 201916

About Kevin M. Hellman

Kevin M. Hellman is a scholar working on Public Health, Environmental and Occupational Health, Cognitive Neuroscience, Physiology, Reproductive Medicine and Cellular and Molecular Neuroscience, having authored 47 papers that have together received 937 indexed citations. Recurring topics across this work include Menstrual Health and Disorders (23 papers), Pain Mechanisms and Treatments (8 papers), Endometriosis Research and Treatment (7 papers), Sleep and Wakefulness Research (6 papers), Neuroscience and Neuropharmacology Research (5 papers), Neuroendocrine regulation and behavior (4 papers), Pelvic floor disorders treatments (4 papers) and Dermatology and Skin Diseases (3 papers). The work is most often cited by research in Endocrine and Autonomic Systems (143 citations), Reproductive Medicine (117 citations), Cognitive Neuroscience (256 citations), Public Health, Environmental and Occupational Health (311 citations) and Behavioral Neuroscience (37 citations). Kevin M. Hellman has collaborated with scholars based in United States, Bulgaria and Belgium. Frequent co-authors include Frank F. Tu, Ted Abel, Folabomi A. Oladosu, Steven Thomas, Ming Ouyang, Peggy Mason, Julie A. Blendy, Allan I Pack, Sigrid C. Veasey and James W. Griffith. Their work appears in journals such as American Journal of Obstetrics and Gynecology, Pain, Journal of Neurophysiology, Molecular Pain and Reproductive Sciences.

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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