Chloë Brown

39 papers receiving 1.2k citations

Chloë Brown's Hit Papers

Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data 2020 · 323 citations
3230+2+4Years since publication100200300

Peers

Chloë Brown
Comparison fields: 5 of 124
  • Signal Processing 237
  • Applied Psychology 86
  • Radiology, Nuclear Medicine and Imaging 298
  • Transportation 92
  • Health Informatics 19
Replace Siddique Latif with:
Siddique Latif Australia
Sérgio Matos Portugal
Aonghus Lawlor Ireland
Ashima Yadav India
Miguel Angel Luengo-Oroz Spain
David T. Borland United States
Eric Fosler‐Lussier United States
Alessio Signorini United States
Stuart Moran United Kingdom
Chloë Brown relative to Siddique Latif Australia Siddique Latif's profile →
Citations per field
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Citations per year

Countries citing papers authored by Chloë Brown

Since Specialization
Citations

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

Fields of papers citing papers by Chloë Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data
Hit paper breakdown →
2020323
2 2016150
3 200595
4 201685
5 202170
6 202269
7 202166
8 201453
9 202052
10 201451
11 199735
12 199834
13 202225
14 201222
15 201321
16 202116
17 199714
18 202314
19 199913
20 201412

About Chloë Brown

Chloë Brown is a scholar working on Transportation, Atomic and Molecular Physics, and Optics, Signal Processing, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 42 papers that have together received 1.3k indexed citations. Recurring topics across this work include Solid State Laser Technologies (11 papers), Human Mobility and Location-Based Analysis (8 papers), Photorefractive and Nonlinear Optics (7 papers), Advanced Fiber Laser Technologies (7 papers), Complex Network Analysis Techniques (5 papers), COVID-19 diagnosis using AI (4 papers), Smoking Behavior and Cessation (4 papers) and Opinion Dynamics and Social Influence (3 papers). The work is most often cited by research in Signal Processing (237 citations), Applied Psychology (86 citations), Radiology, Nuclear Medicine and Imaging (298 citations), Transportation (92 citations) and Health Informatics (19 citations). Chloë Brown has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Cecilia Mascolo, Dimitris Spathis, Pietro Cicuta, Jagmohan Chauhan, Andreas Grammenos, Xia Tong, Jing Han, Apinan Hasthanasombat, Anastasios Noulas and Neal Lathia. Their work appears in journals such as Optics Letters, Journal of Viral Hepatitis, Rheumatology and Therapy, Journal of Medical Internet Research and Applied Physics Letters.

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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