Matthew Greig
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Geriatrics and Gerontology top 10%
Papers in
-
- SARS-CoV-2 and COVID-19 Research 2
- SARS-CoV-2 detection and testing 1
-
- Cardiac, Anesthesia and Surgical Outcomes 1
- Acute Myocardial Infarction Research 1
- Co-authors
- Thomas Dean (1 shared paper)Robert Givan (1 shared paper)Yannick Galipeau (2 shared papers)Marc‐André Langlois (3 shared papers)Matt Driedger (1 shared paper)Chaojie Liu (1 shared paper)Jonathan Hewitt (4 shared papers)Lyndsay Pearce (4 shared papers)
- Journals
- Age and Ageing (1 paper)Frontiers in Immunology (1 paper)Postgraduate Medical Journal (1 paper)EBioMedicine (1 paper)Artificial Intelligence (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Matthew Greig
9 papers receiving 480 citations
Peers
Comparison fields: 5 of 84
- Infectious Diseases 159
- Geriatrics and Gerontology 26
- Artificial Intelligence 161
- Computational Theory and Mathematics 58
- Software 13
Countries citing papers authored by Matthew Greig
This map shows the geographic impact of Matthew Greig'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 Greig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Greig more than expected).
Fields of papers citing papers by Matthew Greig
This network shows the impact of papers produced by Matthew Greig. 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 Greig. The network helps show where Matthew Greig may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Greig, 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 | 2003 | 201 | |
| 2 | 2020 | 167 | |
| 3 | 2016 | 68 | |
| 4 | 2021 | 33 | |
| 5 | 2023 | 8 | |
| 6 | 2013 | 8 | |
| 7 | 2016 | 6 | |
| 8 | 2019 | 4 | |
| 9 | 2017 | 3 |
About Matthew Greig
Matthew Greig is a scholar working on Infectious Diseases, Cardiology and Cardiovascular Medicine, Critical Care and Intensive Care Medicine, Virology and Pulmonary and Respiratory Medicine, having authored 9 papers that have together received 498 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (2 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (1 paper), Venous Thromboembolism Diagnosis and Management (1 paper), SARS-CoV-2 detection and testing (1 paper), Bayesian Modeling and Causal Inference (1 paper), Intensive Care Unit Cognitive Disorders (1 paper), Cardiac, Anesthesia and Surgical Outcomes (1 paper) and Acute Myocardial Infarction Research (1 paper). The work is most often cited by research in Infectious Diseases (159 citations), Geriatrics and Gerontology (26 citations), Artificial Intelligence (161 citations), Computational Theory and Mathematics (58 citations) and Software (13 citations). Matthew Greig has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Thomas Dean, Robert Givan, Yannick Galipeau, Marc‐André Langlois, Matt Driedger, Chaojie Liu, Jonathan Hewitt, Lyndsay Pearce, Phyo Kyaw Myint and Susan Moug. Their work appears in journals such as Age and Ageing, Frontiers in Immunology, Postgraduate Medical Journal, EBioMedicine and Artificial Intelligence.
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.