Jean-Baptiste Courrèges

479 total citations
6 papers, 124 citations indexed

About

Jean-Baptiste Courrèges is a scholar working on Pulmonary and Respiratory Medicine, Rheumatology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jean-Baptiste Courrèges has authored 6 papers receiving a total of 124 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pulmonary and Respiratory Medicine, 3 papers in Rheumatology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jean-Baptiste Courrèges's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Sarcoma Diagnosis and Treatment (3 papers) and Soft tissue tumor case studies (3 papers). Jean-Baptiste Courrèges is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Sarcoma Diagnosis and Treatment (3 papers) and Soft tissue tumor case studies (3 papers). Jean-Baptiste Courrèges collaborates with scholars based in France and United States. Jean-Baptiste Courrèges's co-authors include Jean‐Michel Coindre, Jean‐Yves Blay, Sylvie Bonvalot, Philippe Terrier, Antoîne Italiano, Y Robin, Nicolás Isambert, Florence Duffaud, François Bertucci and Dominique Ranchère‐Vince and has published in prestigious journals such as Cancer Research, Scientific Reports and The American Journal of Surgical Pathology.

In The Last Decade

Jean-Baptiste Courrèges

4 papers receiving 122 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jean-Baptiste Courrèges France 3 100 74 55 31 17 6 124
Christina Baumgarten Germany 3 160 1.6× 110 1.5× 77 1.4× 55 1.8× 17 1.0× 4 167
C. Diéval France 4 68 0.7× 68 0.9× 32 0.6× 9 0.3× 17 1.0× 8 162
Michael S. Gibson United Kingdom 2 153 1.5× 185 2.5× 30 0.5× 7 0.2× 5 0.3× 5 220
Toufik Bouhadiba France 6 33 0.3× 91 1.2× 17 0.3× 22 0.7× 3 0.2× 19 136
Gary John V. Mercado Philippines 3 33 0.3× 18 0.2× 47 0.9× 32 1.0× 22 1.3× 11 153
Danique L. M. van Broekhoven Netherlands 9 371 3.7× 258 3.5× 186 3.4× 122 3.9× 50 2.9× 9 385
Catrin Wigley United Kingdom 6 61 0.6× 97 1.3× 13 0.2× 5 0.2× 8 0.5× 13 149
Caroline Park Belgium 2 31 0.3× 16 0.2× 54 1.0× 43 1.4× 2 0.1× 6 102
William J. Harb United States 4 45 0.5× 127 1.7× 21 0.4× 5 0.2× 3 0.2× 9 168
Vittoria Colia Italy 7 96 1.0× 92 1.2× 11 0.2× 5 0.2× 7 0.4× 11 164

Countries citing papers authored by Jean-Baptiste Courrèges

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Baptiste Courrèges

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Baptiste Courrèges. 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 Jean-Baptiste Courrèges. The network helps show where Jean-Baptiste Courrèges may publish in the future.

Co-authorship network of co-authors of Jean-Baptiste Courrèges

This figure shows the co-authorship network connecting the top 25 collaborators of Jean-Baptiste Courrèges. A scholar is included among the top collaborators of Jean-Baptiste Courrèges 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 Jean-Baptiste Courrèges. Jean-Baptiste Courrèges is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
1.
Maussion, Charles, Jean‐Michel Coindre, Jean-Yves Blay, et al.. (2025). Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile. Scientific Reports. 15(1). 36588–36588.
2.
Fu, Yu, Marie Karanian, Raul Perret, et al.. (2023). Deep learning predicts patients outcome and mutations from digitized histology slides in gastrointestinal stromal tumor. npj Precision Oncology. 7(1). 71–71. 10 indexed citations
3.
Maussion, Charles, Jean‐Michel Coindre, Jean‐Yves Blay, et al.. (2022). Abstract 1939: Multimodal prediction of metastatic relapse using federated deep learning outperforms state-of-the-art methods in soft-tissue sarcoma. Cancer Research. 82(12_Supplement). 1939–1939.
4.
Masliah‐Planchon, Julien, Sophie Le Guellec, Martine Trassard, et al.. (2020). Lower Rate of CTNNB1 Mutations and Higher Rate of APC Mutations in Desmoid Fibromatosis of the Breast. The American Journal of Surgical Pathology. 44(9). 1266–1273. 13 indexed citations
5.
Penel, Nicolas, Jean‐Michel Coindre, Sylvie Bonvalot, et al.. (2016). Management of desmoid tumours: A nationwide survey of labelled reference centre networks in France. European Journal of Cancer. 58. 90–96. 100 indexed citations
6.
Penel, Nicolas, Jean‐Michel Coindre, A. Le Cesne, et al.. (2015). 3400 Management of Desmoid Tumours (DT): A nationwide survey after labeling of 2 expert networks (RRePS and NetSarc). European Journal of Cancer. 51. S688–S688. 1 indexed citations

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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