Raphaël Favory

7.5k citations
71 papers · 2.3k indexed · h-index 24

Impact in

Papers in

Raphaël Favory

66 papers receiving 2.3k citations

Peers

Raphaël Favory
Comparison fields: 5 of 130
  • Critical Care and Intensive Care Medicine 676
  • Emergency Medicine 359
  • Epidemiology 922
  • Nephrology 168
  • Applied Microbiology and Biotechnology 45
Replace Αναστασία Κοτανίδου with:
Αναστασία Κοτανίδου Greece
Kazuma Yamakawa Japan
Yannick Mallédant France
Satoshi Fujimi Japan
Yves Debaveye Belgium
Naoki Aikawa Japan
Samir Jamali France
Stefan Hofer Germany
Eduardo Tamayo Spain
Thorsten Brenner Germany
Raphaël Favory relative to Αναστασία Κοτανίδου Greece Αναστασία Κοτανίδου's profile →
Citations per field
00.5×1.6×
Αναστασία Κοτανίδου · 1×
Citations per year

Countries citing papers authored by Raphaël Favory

Since Specialization
Citations

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

Fields of papers citing papers by Raphaël Favory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20235
2 20234
3 20233
4 202318
5 202021
6 202024
7 20188
8 20174
9 201769
10 201440
11 20148
12 201462
13 20138
14 2013154
15 201155
16 2008122
17 200639
18 200684
19 200618
20 20042

About Raphaël Favory

Raphaël Favory is a scholar working on Critical Care and Intensive Care Medicine, Emergency Medicine, Internal Medicine, Epidemiology and Nephrology, having authored 71 papers that have together received 2.3k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (30 papers), Cardiac Arrest and Resuscitation (12 papers), Hemodynamic Monitoring and Therapy (12 papers), Intensive Care Unit Cognitive Disorders (8 papers), Heme Oxygenase-1 and Carbon Monoxide (7 papers), Respiratory Support and Mechanisms (6 papers), Renal function and acid-base balance (6 papers) and Mitochondrial Function and Pathology (5 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (676 citations), Emergency Medicine (359 citations), Epidemiology (922 citations), Nephrology (168 citations) and Applied Microbiology and Biotechnology (45 citations). Raphaël Favory has collaborated with scholars based in France, Belgium and United States. Frequent co-authors include Rémi Nevière, Daniel De Backer, Jean‐Louis Vincent, Steve Lancel, Diamantino Salgado, Jacques Créteur, Daniel Mathieu, Brigitte Decoster, Sidi Mohamed Hassoun and Saad Nseir. Their work appears in journals such as Critical Care, Annals of Intensive Care, Critical Care Medicine, Shock and Intensive Care Medicine.

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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