Matthew Greig
Impact in
- Geriatrics and Gerontology top 10%
- Frailty in Older Adults
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
-
- SARS-CoV-2 and COVID-19 Research 2
- COVID-19 Clinical Research Studies 2
- HIV/AIDS Research and Interventions 1
-
- Frailty in Older Adults 3
- Co-authors
- Thomas Dean (1 shared paper)Robert Givan (1 shared paper)Marc‐André Langlois (3 shared papers)Yannick Galipeau (2 shared papers)Chaojie Liu (1 shared paper)Michael Stechman (4 shared papers)Susan Moug (4 shared papers)Kathryn McCarthy (4 shared papers)
- Journals
- Artificial Intelligence (1 paper)BMJ Open (1 paper)Nature Communications (1 paper)Frontiers in Immunology (1 paper)EBioMedicine (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Matthew Greig
9 papers receiving 434 citations
Peers
Comparison fields: 5 of 86
- Geriatrics and Gerontology 39
- Infectious Diseases 175
- Artificial Intelligence 133
- Modeling and Simulation 16
- Computational Theory and Mathematics 43
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 | 167 | |
| 2 | 2020 | 160 | |
| 3 | 2016 | 65 | |
| 4 | 2021 | 32 | |
| 5 | 2023 | 7 | |
| 6 | 2013 | 7 | |
| 7 | 2016 | 6 | |
| 8 | 2019 | 4 | |
| 9 | 2017 | 3 |
About Matthew Greig
Matthew Greig is a scholar working on Infectious Diseases, Geriatrics and Gerontology, Cardiology and Cardiovascular Medicine, Surgery and Critical Care and Intensive Care Medicine, having authored 9 papers that have together received 451 indexed citations. Recurring topics across this work include Frailty in Older Adults (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), COVID-19 Clinical Research Studies (2 papers), HIV Research and Treatment (1 paper), Bayesian Modeling and Causal Inference (1 paper), Atrial Fibrillation Management and Outcomes (1 paper), HIV/AIDS Research and Interventions (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Geriatrics and Gerontology (39 citations), Infectious Diseases (175 citations), Artificial Intelligence (133 citations), Modeling and Simulation (16 citations) and Computational Theory and Mathematics (43 citations). Matthew Greig has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Thomas Dean, Robert Givan, Marc‐André Langlois, Yannick Galipeau, Chaojie Liu, Michael Stechman, Susan Moug, Kathryn McCarthy, Lyndsay Pearce and Phyo Kyaw Myint. Their work appears in journals such as Artificial Intelligence, BMJ Open, Nature Communications, Frontiers in Immunology and EBioMedicine.
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.