Anaïs Scohy

1.5k citations
26 papers · 665 indexed · 1 hit paper · h-index 11

Anaïs Scohy

25 papers receiving 661 citations

Hit Papers

Low performance of rapid antigen detection test as frontl...4082020202620222024100200300400

Peers

Anaïs Scohy
Comparison fields: 5 of 85
  • Infectious Diseases 504
  • Transplantation 35
  • Modeling and Simulation 24
  • Biomedical Engineering 207
  • Health Informatics 6
Replace Shinae Yu with:
Shinae Yu South Korea
Owen Tak‐Yin Tsang Hong Kong
Sonia N. Rao United States
Ann E. Woolley United States
Emily MacLean Canada
Tommy Hing‐Cheung Tang China
Donia Bouzid France
Gregory Pepper United States
Ellen H. Lee United States
Josep Pareja Spain
Anaïs Scohy relative to Shinae Yu South Korea Shinae Yu's profile →
Citations per field
00.5×6.9×
Shinae Yu · 1×
Citations per year

Countries citing papers authored by Anaïs Scohy

Since Specialization
Citations

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

Fields of papers citing papers by Anaïs Scohy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20233
3 20237
4 20233
5 202214
6 202223
7 202210
8 20212
9 20211
10 20213
11 20217
12 20213
13 202117
14 20206
15 202010
16
Low performance of rapid antigen detection test as frontline testing for COVID-19 diagnosisbreakdown →
2020408
17 202033
18 20187
19 201825
20 201332

About Anaïs Scohy

Anaïs Scohy is a scholar working on Microbiology, Infectious Diseases and Modeling and Simulation, having authored 26 papers that have together received 665 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (16 papers), COVID-19 Clinical Research Studies (16 papers), SARS-CoV-2 detection and testing (7 papers), Long-Term Effects of COVID-19 (6 papers), COVID-19 epidemiological studies (2 papers), Pneumocystis jirovecii pneumonia detection and treatment (2 papers), Biosensors and Analytical Detection (2 papers) and COVID-19 and healthcare impacts (2 papers). The work is most often cited by research in Infectious Diseases (504 citations), Transplantation (35 citations) and Modeling and Simulation (24 citations). Anaïs Scohy has collaborated with scholars based in Belgium, France and United Kingdom. Frequent co-authors include Hector Rodriguez‐Villalobos, Alexia Verroken, Benoît Kabamba‐Mukadi, Ahalieyah Anantharajah, Monique Bodéus, Jean Cyr Yombi, Leïla Belkhir, Julien De Greef, Benoît Kabamba and Éric Goffin. Their work appears in journals such as Scientific Reports, Transplantation and Journal of Medical Virology.

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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