Matthew Wiley
Impact in
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- Artificial Intelligence in Healthcare
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- Diabetes Management and Research
Papers in
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- Artificial Intelligence in Healthcare 4
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- Machine Learning in Healthcare 2
- Co-authors
- Vagelis Hristidis (5 shared papers)Jean C. Beckham (3 shared papers)Patrick S. Calhoun (3 shared papers)Frank Schwartz (3 shared papers)Jay H. Shubrook (3 shared papers)Michelle F. Dennis (2 shared papers)Cynthia R. Marling (1 shared paper)F. Joseph McClernon (1 shared paper)
- Journals
- Journal of Medical Internet Research (2 papers)Journal of Biomedical Informatics (2 papers)Nicotine & Tobacco Research (1 paper)Journal of Diabetes Science and Technology (1 paper)AI Magazine (1 paper)
- Partner nations
- United StatesAustraliaNew Zealand
In The Last Decade
Matthew Wiley
15 papers receiving 328 citations
Peers
Comparison fields: 5 of 78
- Health Information Management 31
- Endocrinology, Diabetes and Metabolism 63
- Health 26
- Clinical Psychology 56
- Applied Psychology 10
Countries citing papers authored by Matthew Wiley
This map shows the geographic impact of Matthew Wiley'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 Matthew Wiley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Wiley more than expected).
Fields of papers citing papers by Matthew Wiley
This network shows the impact of papers produced by Matthew Wiley. 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 Matthew Wiley. The network helps show where Matthew Wiley may publish in the future.
Co-authors
The 23 scholars most cited alongside Matthew Wiley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 57 | |
| 2 | 2008 | 55 | |
| 3 | 2015 | 49 | |
| 4 | 2016 | 33 | |
| 5 | 2015 | 33 | |
| 6 | 2014 | 31 | |
| 7 | 2009 | 28 | |
| 8 | 2012 | 23 | |
| 9 | 2008 | 19 | |
| 10 | Machine Learning for Diabetes Decision Support | 2011 | 8 |
| 11 | 2016 | 4 | |
| 12 | 2013 | 3 | |
| 13 | 2011 | 1 | |
| 14 | 2017 | 1 | |
| 15 | Ontology-Based Analysis of Online Healthcare Data | 2016 | 1 |
About Matthew Wiley
Matthew Wiley is a scholar working on Health Information Management, Artificial Intelligence, Molecular Biology, Health and General Health Professions, having authored 15 papers that have together received 346 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (4 papers), Machine Learning in Healthcare (2 papers), Biomedical Text Mining and Ontologies (2 papers), Smoking Behavior and Cessation (2 papers), Social Media in Health Education (2 papers), Diabetes Management and Research (1 paper), Writing and Handwriting Education (1 paper) and Healthcare professionals’ stress and burnout (1 paper). The work is most often cited by research in Health Information Management (31 citations), Endocrinology, Diabetes and Metabolism (63 citations), Health (26 citations), Clinical Psychology (56 citations) and Applied Psychology (10 citations). Matthew Wiley has collaborated with scholars based in United States, Australia and New Zealand. Frequent co-authors include Vagelis Hristidis, Jean C. Beckham, Patrick S. Calhoun, Frank Schwartz, Jay H. Shubrook, Michelle F. Dennis, Cynthia R. Marling, F. Joseph McClernon, Kevin Esterling and Canghong Jin. Their work appears in journals such as Journal of Medical Internet Research, Journal of Biomedical Informatics, Nicotine & Tobacco Research, Journal of Diabetes Science and Technology and AI Magazine.
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.