Peter Leese
Impact in
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- Obesity and Health Practices
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- Workplace Health and Well-being
- Employment and Welfare Studies
- Global Health Care Issues
Papers in
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- Chronic Disease Management Strategies 2
- Sepsis Diagnosis and Treatment 1
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- Machine Learning in Healthcare 3
- Co-authors
- Deborah F. Tate (1 shared paper)Laura Linnan (1 shared paper)Eric Finkelstein (1 shared paper)Emily Pfaff (3 shared papers)Richard A. Moffitt (3 shared papers)Melissa Haendel (3 shared papers)John B. Buse (1 shared paper)Andrew T. Girvin (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (2 papers)BMJ Open Diabetes Research & Care (1 paper)Journal of Occupational and Environmental Medicine (1 paper)npj Digital Medicine (1 paper)Communications Medicine (1 paper)
- Partner nations
- United StatesSingapore
In The Last Decade
Peter Leese
4 papers receiving 37 citations
Peers
Comparison fields: 5 of 30
- Pharmacy 4
- General Health Professions 20
- Health Information Management 3
- Experimental and Cognitive Psychology 8
- Occupational Therapy 2
Countries citing papers authored by Peter Leese
This map shows the geographic impact of Peter Leese'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 Peter Leese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Leese more than expected).
Fields of papers citing papers by Peter Leese
This network shows the impact of papers produced by Peter Leese. 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 Peter Leese. The network helps show where Peter Leese may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Leese, 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 | 2009 | 33 | |
| 2 | 2023 | 5 | |
| 3 | 2024 | 2 | |
| 4 | 2025 | 1 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 0 |
About Peter Leese
Peter Leese is a scholar working on Epidemiology, Artificial Intelligence, Surgery, Molecular Biology and Neurology, having authored 6 papers that have together received 41 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (3 papers), Chronic Disease Management Strategies (2 papers), Sepsis Diagnosis and Treatment (1 paper), Long-Term Effects of COVID-19 (1 paper), Metabolism, Diabetes, and Cancer (1 paper), Diabetes Treatment and Management (1 paper), Fibromyalgia and Chronic Fatigue Syndrome Research (1 paper) and Lipoproteins and Cardiovascular Health (1 paper). The work is most often cited by research in Pharmacy (4 citations), General Health Professions (20 citations), Health Information Management (3 citations), Experimental and Cognitive Psychology (8 citations) and Occupational Therapy (2 citations). Peter Leese has collaborated with scholars based in United States and Singapore. Frequent co-authors include Deborah F. Tate, Laura Linnan, Eric Finkelstein, Emily Pfaff, Richard A. Moffitt, Melissa Haendel, John B. Buse, Andrew T. Girvin, John Powers and Hannah Davis. Their work appears in journals such as Journal of the American Medical Informatics Association, BMJ Open Diabetes Research & Care, Journal of Occupational and Environmental Medicine, npj Digital Medicine and Communications Medicine.
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.