Raphaël Couronné

26 total papers · 1.0k total citations
8 papers, 645 citations indexed

About

Raphaël Couronné is a scholar working on Neurology, Artificial Intelligence and Physiology. According to data from OpenAlex, Raphaël Couronné has authored 8 papers receiving a total of 645 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Neurology, 3 papers in Artificial Intelligence and 2 papers in Physiology. Recurrent topics in Raphaël Couronné's work include Parkinson's Disease Mechanisms and Treatments (3 papers), Machine Learning in Healthcare (2 papers) and Dementia and Cognitive Impairment Research (2 papers). Raphaël Couronné is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (3 papers), Machine Learning in Healthcare (2 papers) and Dementia and Cognitive Impairment Research (2 papers). Raphaël Couronné collaborates with scholars based in France, Germany and United Kingdom. Raphaël Couronné's co-authors include Anne‐Laure Boulesteix, Philipp Probst, Stanley Durrleman, Jean‐Christophe Corvol, Stéphane Epelbaum, Marie Vidailhet, Johann Faouzi, Junhao Wen, Elina Thibeau–Sutre and Alexandre Bône and has published in prestigious journals such as Annals of Neurology, BMC Bioinformatics and Movement Disorders.

In The Last Decade

Raphaël Couronné

8 papers receiving 625 citations

Hit Papers

Random forest versus logi... 2018 2026 2020 2023 2018 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Raphaël Couronné 126 61 59 59 52 8 645
Ilse Kant 160 1.3× 58 1.0× 72 1.2× 45 0.8× 48 0.9× 32 784
Damjan Krstajić 109 0.9× 26 0.4× 40 0.7× 22 0.4× 59 1.1× 8 774
Suleman Atique 57 0.5× 80 1.3× 53 0.9× 46 0.8× 36 0.7× 34 781
Yolande Tra 42 0.3× 43 0.7× 45 0.8× 69 1.2× 54 1.0× 16 709
Gehad El Ashal 43 0.3× 22 0.4× 31 0.5× 61 1.0× 45 0.9× 15 583
Andrius Budrionis 164 1.3× 18 0.3× 35 0.6× 105 1.8× 44 0.8× 32 755
Lampros Kourtis 43 0.3× 123 2.0× 47 0.8× 164 2.8× 141 2.7× 15 688
Luca Foschini 207 1.6× 16 0.3× 87 1.5× 33 0.6× 48 0.9× 28 682
Ashin Mukherjee 94 0.7× 25 0.4× 46 0.8× 32 0.5× 14 0.3× 6 575
Ciprian Crainiceanu 58 0.5× 33 0.5× 36 0.6× 36 0.6× 27 0.5× 26 697

Countries citing papers authored by Raphaël Couronné

Since Specialization
Citations

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

Fields of papers citing papers by Raphaël Couronné

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raphaël Couronné

This figure shows the co-authorship network connecting the top 25 collaborators of Raphaël Couronné. A scholar is included among the top collaborators of Raphaël Couronné based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raphaël Couronné. Raphaël Couronné is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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