Mark E. Epstein

507 citations
7 papers · 283 · h-index 5

Impact in

  • Equine top 2%
    • Veterinary Equine Medical Research
    • Veterinary Pharmacology and Anesthesia
    • Veterinary Orthopedics and Neurology

Papers in

Mark E. Epstein

6 papers receiving 263 citations

Peers

Mark E. Epstein
Comparison fields: 5 of 76
  • Equine 52
  • Small Animals 157
  • Virology 42
  • Parasitology 57
  • Anesthesiology and Pain Medicine 18
Replace Andrea L. Looney with:
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Yael Shilo‐Benjamini Israel
Reuben E. Merideth United States
Livia Benato United Kingdom
Masoud Selk Ghaffari Iran
Mark E. Epstein relative to Andrea L. Looney United States Andrea L. Looney's profile →
Citations per field
00.5×4.1×
Andrea L. Looney · 1×
Citations per year

Countries citing papers authored by Mark E. Epstein

Since Specialization
Citations

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

Fields of papers citing papers by Mark E. Epstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Mark E. Epstein, 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 Mark E. Epstein Line = papers co-authored together Mark E. Epstein links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2015184
2 198971
3 200811
4
Statistical source channel models for natural language understanding
19969
5 20204
6
A module architecture for an integrated multi-robot system
19843
7 20141

About Mark E. Epstein

Mark E. Epstein is a scholar working on Small Animals, Surgery, Artificial Intelligence, Physiology and Virology, having authored 7 papers that have together received 283 indexed citations. Recurring topics across this work include Veterinary Pharmacology and Anesthesia (3 papers), Pain Mechanisms and Treatments (2 papers), Natural Language Processing Techniques (2 papers), Anesthesia and Pain Management (2 papers), Speech and dialogue systems (2 papers), Rabies epidemiology and control (1 paper), Herpesvirus Infections and Treatments (1 paper) and Toxoplasma gondii Research Studies (1 paper). The work is most often cited by research in Equine (52 citations), Small Animals (157 citations), Virology (42 citations), Parasitology (57 citations) and Anesthesiology and Pain Medicine (18 citations). Mark E. Epstein has collaborated with scholars based in United States. Frequent co-authors include Sheilah A. Robertson, M.C. Petty, Gregg M. Griffenhagen, Wendy Simpson, Craig E. Greene, Ralph Grishman, Gerasimos Potamianos, Kang G. Shin and Richard A. Volz. Their work appears in journals such as Topics in companion animal medicine, Veterinary Clinics of North America Small Animal Practice, Journal of Feline Medicine and Surgery, Journal of Veterinary Internal Medicine and Deep Blue (University of Michigan).

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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