Mark Donnelly

87 papers receiving 786 citations

Peers

Mark Donnelly
Comparison fields: 5 of 112
  • Computer Vision and Pattern Recognition 220
  • Occupational Therapy 37
  • Demography 111
  • Cardiology and Cardiovascular Medicine 177
  • Human-Computer Interaction 42
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François Portet France
Bruno M. C. Silva Portugal
Ivan Chorbev North Macedonia
Valérie Gay Australia
Vincent Rialle France
Peter Leijdekkers Australia
Bessam Abdulrazak Canada
Katarzyna Wac Switzerland
Farhaan Mirza New Zealand
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Citations per field
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Citations per year

Countries citing papers authored by Mark Donnelly

Since Specialization
Citations

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

Fields of papers citing papers by Mark Donnelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201351
2 201344
3 200740
4 200840
5 201229
6 200629
7 201028
8 200827
9 201025
10 201623
11 200822
12 200921
13 201220
14 201819
15 201018
16 200718
17 200816
18 201816
19 201915
20 201815

About Mark Donnelly

Mark Donnelly is a scholar working on Computer Vision and Pattern Recognition, Demography, Cardiology and Cardiovascular Medicine, Artificial Intelligence and Cognitive Neuroscience, having authored 94 papers that have together received 815 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (22 papers), Technology Use by Older Adults (19 papers), ECG Monitoring and Analysis (15 papers), Dementia and Cognitive Impairment Research (10 papers), Cardiac electrophysiology and arrhythmias (9 papers), Mobile Health and mHealth Applications (9 papers), EEG and Brain-Computer Interfaces (9 papers) and Data Stream Mining Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Occupational Therapy (37 citations), Demography (111 citations), Cardiology and Cardiovascular Medicine (177 citations) and Human-Computer Interaction (42 citations). Mark Donnelly has collaborated with scholars based in United Kingdom, Ireland and United States. Frequent co-authors include Chris Nugent, Dewar Finlay, N.D. Black, Sally McClean, Paul McCullagh, Bryan Scotney, Ian Cleland, David Craig, Liming Chen and Leo Galway. Their work appears in journals such as Pervasive and Mobile Computing, IEEE Pervasive Computing, International Journal of Language & Communication Disorders, BMJ Open and BMC Medical Informatics and Decision Making.

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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