C.A. Cuénod

6.6k citations
138 papers · 4.9k indexed · h-index 38

C.A. Cuénod

133 papers receiving 4.8k citations

Peers

C.A. Cuénod
Comparison fields: 5 of 149
  • Radiology, Nuclear Medicine and Imaging 2.5k
  • Obstetrics and Gynecology 833
  • Reproductive Medicine 638
  • Hepatology 280
  • Cognitive Neuroscience 602
Replace Toshihide Ogawa with:
Toshihide Ogawa Japan
Élodie Breton France
Pek‐Lan Khong Hong Kong
Nathan McDannold United States
D Lallemand France
Mutsumasa Takahashi Japan
Mijin Yun South Korea
Harumi Sakahara Japan
Sven N. Reske Germany
Bruno Beomonte Zobel Italy
C.A. Cuénod relative to Toshihide Ogawa Japan Toshihide Ogawa's profile →
Citations per field
00.5×3.1×
Toshihide Ogawa · 1×
Citations per year

Countries citing papers authored by C.A. Cuénod

Since Specialization
Citations

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

Fields of papers citing papers by C.A. Cuénod

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20193
2 201915
3 20181
4 201728
5 201635
6 201449
7 20138
8 201312
9 201226
10 2012162
11 201025
12 201016
13 200532
14 200432
15 200120
16 199830
17 199842
18 19962
19 1996154
20 199359

About C.A. Cuénod

C.A. Cuénod is a scholar working on Obstetrics and Gynecology, Radiology, Nuclear Medicine and Imaging, Microbiology, Reproductive Medicine and Pediatrics, Perinatology and Child Health, having authored 138 papers that have together received 4.9k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (56 papers), Advanced MRI Techniques and Applications (36 papers), Pregnancy and preeclampsia studies (17 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Medical Imaging Techniques and Applications (11 papers), Renal cell carcinoma treatment (10 papers), Ovarian cancer diagnosis and treatment (9 papers) and Ultrasound and Hyperthermia Applications (8 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.5k citations), Obstetrics and Gynecology (833 citations), Reproductive Medicine (638 citations), Hepatology (280 citations) and Cognitive Neuroscience (602 citations). C.A. Cuénod has collaborated with scholars based in France, United States and Belgium. Frequent co-authors include Daniel Balvay, Olivier Clémеnt, Laure Fournier, Nathalie Siauve, Denis Le Bihan, Isabelle Thomassin‐Naggara, Guy Frija, Émile Daraï, Marc Bazot and Thomas A. Zeffiro. Their work appears in journals such as Radiology, European Radiology, Magnetic Resonance Imaging, Magnetic Resonance in Medicine and Academic Radiology.

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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