Scott Doyle

83 papers receiving 2.7k citations

Peers

Scott Doyle
Comparison fields: 5 of 149
  • Biophysics 282
  • Transportation 286
  • Artificial Intelligence 1.3k
  • Computer Vision and Pattern Recognition 757
  • Radiology, Nuclear Medicine and Imaging 656
Replace Ming Y. Lu with:
Ming Y. Lu United States
Arunachalam Narayanaswamy United States
Lisa Tang Canada
George C. Linderman United States
Ying Zhuge United States
Derek Wu Canada
Richard J. Chen United States
Jorge Cuadros United States
Sam Li‐Sheng Chen Taiwan
T. Madams United States
Scott Doyle relative to Ming Y. Lu United States Ming Y. Lu's profile →
Citations per field
00.5×20×40×60×71.5×
Ming Y. Lu · 1×
Citations per year

Countries citing papers authored by Scott Doyle

Since Specialization
Citations

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

Fields of papers citing papers by Scott Doyle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008243
2 2006242
3 2010207
4 2008204
5 2014201
6 2007174
7 2018156
8 2004120
9 200896
10 201194
11 200685
12 201280
13 200379
14 201874
15 201152
16 201051
17 201848
18 201641
19 200932
20 200830

About Scott Doyle

Scott Doyle is a scholar working on Health Informatics, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 87 papers that have together received 2.8k indexed citations. Recurring topics across this work include AI in cancer detection (33 papers), Radiomics and Machine Learning in Medical Imaging (13 papers), Medical Image Segmentation Techniques (10 papers), Digital Imaging for Blood Diseases (10 papers), Medical Imaging and Analysis (7 papers), Gene expression and cancer classification (7 papers), Asthma and respiratory diseases (6 papers) and Image Retrieval and Classification Techniques (6 papers). The work is most often cited by research in Biophysics (282 citations), Transportation (286 citations), Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (757 citations) and Radiology, Nuclear Medicine and Imaging (656 citations). Scott Doyle has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Anant Madabhushi, Michael D. Feldman, John Tomaszewski, Shannon C. Agner, Marc Schlossberg, Jean Stockard, John Tomaszeweski, Christos V. Ioannou, Mark Speakman and Roger Kirby. Their work appears in journals such as Value in Health, Journal of Pathology Informatics, Journal of Pediatric Orthopaedics, The Laryngoscope and The FASEB Journal.

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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