Thomas E. Doyle

63 papers receiving 786 citations

Thomas E. Doyle's Hit Papers

MLCM: Multi-Label Confusion Matrix 2022 · 284 citations
2840+1+2Years since publication50100150200250

Peers

Thomas E. Doyle
Comparison fields: 5 of 119
  • Health Informatics 88
  • Health Information Management 74
  • Architecture 28
  • Human-Computer Interaction 34
  • Computer Vision and Pattern Recognition 93
Replace Avid Roman–Gonzalez with:
Avid Roman–Gonzalez Peru
Abdelilah Jilbab Morocco
Thanos G. Stavropoulos Greece
Míriam Antón‐Rodríguez Spain
Francisco Javier Díaz Pernas Spain
Mobyen Uddin Ahmed Sweden
Madalina Fiterau United States
Jasper Snoek Canada
Oh Shu Lih Singapore
Sara Colantonio Italy
Thomas E. Doyle relative to Avid Roman–Gonzalez Peru Avid Roman–Gonzalez's profile →
Citations per field
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Avid Roman–Gonzalez · 1×
Citations per year

Countries citing papers authored by Thomas E. Doyle

Since Specialization
Citations

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

Fields of papers citing papers by Thomas E. Doyle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MLCM: Multi-Label Confusion Matrix
Hit paper breakdown →
2022284
2 202184
3 201543
4 202129
5 201225
6 202225
7 201724
8 201924
9 201921
10 200617
11 201814
12 201212
13 202412
14 202211
15 202211
16 202311
17 201110
18 20029
19 20119
20 20168

About Thomas E. Doyle

Thomas E. Doyle is a scholar working on Architecture, Health Informatics, Artificial Intelligence, Health Information Management and Signal Processing, having authored 67 papers that have together received 815 indexed citations. Recurring topics across this work include Engineering Education and Pedagogy (8 papers), Artificial Intelligence in Healthcare and Education (7 papers), Artificial Intelligence in Healthcare (5 papers), Machine Learning in Healthcare (4 papers), Spaceflight effects on biology (3 papers), Electrohydrodynamics and Fluid Dynamics (3 papers), Space Exploration and Technology (3 papers) and Evaluation of Teaching Practices (3 papers). The work is most often cited by research in Health Informatics (88 citations), Health Information Management (74 citations), Architecture (28 citations), Human-Computer Interaction (34 citations) and Computer Vision and Pattern Recognition (93 citations). Thomas E. Doyle has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Reza Samavi, Mohammadreza Heydarian, Joan Saary, Matiar M. R. Howlader, William D. Greason, David M Musson, Michael D. Noseworthy, Katherine Zukotynski, Joseph R. Kish and Steven Yule. Their work appears in journals such as IEEE Access, Artificial Intelligence in Medicine, IEEE Transactions on Industry Applications, Microelectronics Reliability and Sensors and Actuators B Chemical.

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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