Éric Salvat

37 papers receiving 1.2k citations

Éric Salvat's Hit Papers

Pharmacological and non-pharmacological treatments for neuropathic pain: Systematic review and French recommendations 2020 · 269 citations
2690+2+4Years since publication50100150200250

Peers

Éric Salvat
Comparison fields: 5 of 113
  • Anesthesiology and Pain Medicine 117
  • Physiology 496
  • Computer Networks and Communications 276
  • Neurology 150
  • Artificial Intelligence 381
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Dylan Chou Taiwan
Bernhard Riedl Germany
Yu‐Chuan Tsai Taiwan
Bernd Walter Germany
Rǎjesh C. Sachdeo United States
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Kazuo Ushijima Japan
Huan Gui China
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Citations per year

Countries citing papers authored by Éric Salvat

Since Specialization
Citations

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

Fields of papers citing papers by Éric Salvat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Pharmacological and non-pharmacological treatments for neuropathic pain: Systematic review and French recommendations
Hit paper breakdown →
2020269
2 2016215
3 2011188
4 199677
5 201871
6
Extending decidable cases for rules with existential variables
200963
7 201460
8 199831
9 201330
10 201630
11 201627
12 201922
13 202121
14 201421
15 200616
16 201815
17 201814
18 201713
19 201512
20 202010

About Éric Salvat

Éric Salvat is a scholar working on Physiology, Artificial Intelligence, Computer Networks and Communications, Neurology and Cellular and Molecular Neuroscience, having authored 40 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (18 papers), Semantic Web and Ontologies (12 papers), Advanced Database Systems and Queries (8 papers), Botulinum Toxin and Related Neurological Disorders (7 papers), Data Management and Algorithms (5 papers), Pain Management and Placebo Effect (5 papers), Neuropeptides and Animal Physiology (4 papers) and Pain Management and Opioid Use (3 papers). The work is most often cited by research in Anesthesiology and Pain Medicine (117 citations), Physiology (496 citations), Computer Networks and Communications (276 citations), Neurology (150 citations) and Artificial Intelligence (381 citations). Éric Salvat has collaborated with scholars based in France, Morocco and Germany. Frequent co-authors include Marie-Laure Mugnier, Michel Barrot, İpek Yalçın, Jean-François Baget, Mélanie Kremer, Michel Leclère, André C. Müller, Michel Lantéri‐Minet, Nadine Attal and Salim Megat. Their work appears in journals such as Molecular Pain, European Journal of Pain, European Journal of Medicinal Chemistry, Journal of Visualized Experiments and Knowledge-Based Systems.

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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