Signe Redfield

3.9k citations
19 papers · 1.9k · 1 hit paper · h-index 8

Impact in

Papers in

Signe Redfield

15 papers receiving 1.8k citations

Signe Redfield's Hit Papers

Characterizing long COVID in an international cohort: 7 months of symptoms and their impact 2021 · 1.7k citations
1.7k0+1+3Years since publication50010001.5k

Peers

Signe Redfield
Comparison fields: 5 of 115
  • Neurology 1.5k
  • Critical Care and Intensive Care Medicine 457
  • Clinical Psychology 730
  • Infectious Diseases 506
  • Psychiatry and Mental health 359
Replace Óscar J. Pellicer-Valero with:
Óscar J. Pellicer-Valero Spain
Phang Boon Lim United Kingdom
Marietta Kirchner Germany
Maria Rosaria Barillari Italy
Giovanni Cammaroto Italy
Guillaume Sacco France
Miloš Ajčević Italy
Mohamed Sakel United Kingdom
Matthew A. Koenig United States
Shashank Agarwal United States
Signe Redfield relative to Óscar J. Pellicer-Valero Spain Óscar J. Pellicer-Valero's profile →
Citations per field
00.5×10×12.7×
Óscar J. Pellicer-Valero · 1×
Citations per year

Countries citing papers authored by Signe Redfield

Since Specialization
Citations

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

Fields of papers citing papers by Signe Redfield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1
Characterizing long COVID in an international cohort: 7 months of symptoms and their impact
Hit paper breakdown →
20211687
2 201442
3 201740
4 202139
5 202020
6 201714
7 201212
8 20198
9 20117
10 20043
11 20253
12 20242
13 20222
14 20052
15 20241
16
EFFICIENT OBJECT RECOGNITION USING COLOR QUANTIZATION
20011
17 20191
18 20020
19 20220

About Signe Redfield

Signe Redfield is a scholar working on Neurology, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Clinical Psychology, having authored 19 papers that have together received 1.9k indexed citations. Recurring topics across this work include Long-Term Effects of COVID-19 (6 papers), Respiratory Support and Mechanisms (3 papers), Robotic Path Planning Algorithms (3 papers), Semantic Web and Ontologies (3 papers), COVID-19 and Mental Health (3 papers), Optimization and Search Problems (2 papers), Image Retrieval and Classification Techniques (2 papers) and Robotics and Automated Systems (2 papers). The work is most often cited by research in Neurology (1.5k citations), Critical Care and Intensive Care Medicine (457 citations), Clinical Psychology (730 citations), Infectious Diseases (506 citations) and Psychiatry and Mental health (359 citations). Signe Redfield has collaborated with scholars based in United States, United Kingdom and Portugal. Frequent co-authors include Ryan Low, Hannah Davis, Hannah Wei, Lisa McCorkell, Jared P. Austin, Gina Assaf, Yochai Re’em, Athena Akrami, Paulo Gonçalves and Sandro Rama Fiorini. Their work appears in journals such as IEEE Robotics & Automation Magazine, Journal of Ambient Intelligence and Humanized Computing, Ocean Engineering, Robotics and Computer-Integrated Manufacturing and Cell.

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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