Jonathan D. Kay
Impact in
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- Meta-analysis and systematic reviews
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- Electronic Health Records Systems
Papers in
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- Biomedical Text Mining and Ontologies 1
- Sexual Differentiation and Disorders 1
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- Business Process Modeling and Analysis 1
- Co-authors
- Leigh‐Anne McDuffus (1 shared paper)David E. Neal (1 shared paper)Anne Y. Warren (1 shared paper)Hayley C. Whitaker (2 shared papers)Kevin Paddon (1 shared paper)Kate Goddard (1 shared paper)Abdul Roudsari (1 shared paper)Benjamin S. Simpson (1 shared paper)
- Journals
- The Prostate (1 paper)Annals of Clinical Biochemistry International Journal of Laboratory Medicine (1 paper)Prostate Cancer and Prostatic Diseases (1 paper)Trends in Biochemical Sciences (1 paper)Studies in health technology and informatics (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Jonathan D. Kay
7 papers receiving 29 citations
Peers
Comparison fields: 5 of 25
- Statistics, Probability and Uncertainty 5
- Health Information Management 3
- Family Practice 1
- Physiology 8
- Clinical Biochemistry 2
Countries citing papers authored by Jonathan D. Kay
This map shows the geographic impact of Jonathan D. Kay'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 Jonathan D. Kay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan D. Kay more than expected).
Fields of papers citing papers by Jonathan D. Kay
This network shows the impact of papers produced by Jonathan D. Kay. 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 Jonathan D. Kay. The network helps show where Jonathan D. Kay may publish in the future.
Co-authors
The 20 scholars most cited alongside Jonathan D. Kay, 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 | 2012 | 11 | |
| 2 | 2001 | 5 | |
| 3 | The Oxford clinical intranet: providing clinicians with access to patient records and multiple knowledge bases with internet technology. | 2004 | 5 |
| 4 | 2024 | 3 | |
| 5 | 2010 | 2 | |
| 6 | 1985 | 2 | |
| 7 | 2002 | 1 |
About Jonathan D. Kay
Jonathan D. Kay is a scholar working on Molecular Biology, Management Information Systems, Health Information Management, Urology and Management of Technology and Innovation, having authored 7 papers that have together received 29 indexed citations. Recurring topics across this work include Blood donation and transfusion practices (1 paper), Genomics and Rare Diseases (1 paper), Biomedical Text Mining and Ontologies (1 paper), Muscle metabolism and nutrition (1 paper), Ethics in Clinical Research (1 paper), Sexual Differentiation and Disorders (1 paper), Urological Disorders and Treatments (1 paper) and Business Process Modeling and Analysis (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (5 citations), Health Information Management (3 citations), Family Practice (1 citation), Physiology (8 citations) and Clinical Biochemistry (2 citations). Jonathan D. Kay has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Leigh‐Anne McDuffus, David E. Neal, Anne Y. Warren, Hayley C. Whitaker, Kevin Paddon, Kate Goddard, Abdul Roudsari, Benjamin S. Simpson, Vasilis Stavrinides and Caroline M. Moore. Their work appears in journals such as The Prostate, Annals of Clinical Biochemistry International Journal of Laboratory Medicine, Prostate Cancer and Prostatic Diseases, Trends in Biochemical Sciences and Studies in health technology and informatics.
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.