C. Chabrol

35 papers receiving 1.1k citations

Peers

C. Chabrol
Comparison fields: 5 of 84
  • Radiology, Nuclear Medicine and Imaging 471
  • Cellular and Molecular Neuroscience 224
  • Neurology 67
  • Automotive Engineering 87
  • Neurology 95
Replace Takuya Sakaguchi with:
Takuya Sakaguchi Japan
Yue Wu China
Paolo Emilio Bianchi Italy
Hajime Yagura Japan
John W. Barnard United States
R. de Rooij United States
Dapeng Shi China
Shun Xu China
Johannes Weickenmeier United States
Junhee Lee South Korea
C. Chabrol relative to Takuya Sakaguchi Japan Takuya Sakaguchi's profile →
Citations per field
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Citations per year

Countries citing papers authored by C. Chabrol

Since Specialization
Citations

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

Fields of papers citing papers by C. Chabrol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014118
2 200796
3 201593
4 201387
5 199981
6 201775
7 201459
8 201748
9 201540
10 201639
11 199139
12 201637
13 201733
14 201629
15 201225
16 199222
17 200222
18 201220
19 199920
20
DNA repair enzyme analysis on EWOD fluidic microprocessor
200619

About C. Chabrol

C. Chabrol is a scholar working on Electrical and Electronic Engineering, Radiology, Nuclear Medicine and Imaging, Mechanics of Materials, Cellular and Molecular Neuroscience and Biomedical Engineering, having authored 36 papers that have together received 1.1k indexed citations. Recurring topics across this work include Laser Applications in Dentistry and Medicine (10 papers), Metal and Thin Film Mechanics (8 papers), Photoreceptor and optogenetics research (7 papers), Orthopaedic implants and arthroplasty (5 papers), Microfluidic and Bio-sensing Technologies (4 papers), Transcranial Magnetic Stimulation Studies (4 papers), Tribology and Wear Analysis (4 papers) and Advanced Fiber Optic Sensors (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (471 citations), Cellular and Molecular Neuroscience (224 citations), Neurology (67 citations), Automotive Engineering (87 citations) and Neurology (95 citations). C. Chabrol has collaborated with scholars based in France, Australia and Germany. Frequent co-authors include John Mitrofanis, Napoleon Torrès, Cécile Moro, Nabil El Massri, Alim‐Louis Benabid, Daniel M. Johnstone, Jonathan Stone, Florian Reinhart, Yves Fouillet and Fannie Darlot. Their work appears in journals such as Experimental Brain Research, Journal of Nuclear Materials, Materials Science and Technology, Surface and Coatings Technology and Journal of neurosurgery.

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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