Greg Hapgood
Impact in
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- Lymphoma Diagnosis and Treatment
- Internal Medicine top 10%
- Venous Thromboembolism Diagnosis and Management
Papers in
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- Lymphoma Diagnosis and Treatment 20
- Oncology 8
- Viral-associated cancers and disorders 3
- CAR-T cell therapy research 3
- Co-authors
- Kerry J. Savage (8 shared papers)Erica Malan (1 shared paper)Sanjeev Chunilal (1 shared paper)Diego Villa (5 shared papers)Randy D. Gascoyne (4 shared papers)David W. Scott (4 shared papers)Alina S. Gerrie (4 shared papers)Joseph M. Connors (4 shared papers)
- Journals
- Blood (5 papers)British Journal of Haematology (3 papers)Blood Advances (2 papers)Bioinformatics (1 paper)Thrombosis and Haemostasis (1 paper)
- Partner nations
- AustraliaCanadaUnited Kingdom
In The Last Decade
Greg Hapgood
24 papers receiving 398 citations
Peers
Comparison fields: 5 of 39
- Pathology and Forensic Medicine 216
- Internal Medicine 35
- Dermatology 66
- Oncology 103
- Genetics 36
Countries citing papers authored by Greg Hapgood
This map shows the geographic impact of Greg Hapgood'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 Greg Hapgood with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Hapgood more than expected).
Fields of papers citing papers by Greg Hapgood
This network shows the impact of papers produced by Greg Hapgood. 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 Greg Hapgood. The network helps show where Greg Hapgood may publish in the future.
Co-authors
The 25 scholars most cited alongside Greg Hapgood, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 131 | |
| 2 | 2013 | 73 | |
| 3 | 2018 | 57 | |
| 4 | 2016 | 41 | |
| 5 | 2016 | 20 | |
| 6 | 2015 | 17 | |
| 7 | 2021 | 16 | |
| 8 | 2016 | 10 | |
| 9 | 2018 | 8 | |
| 10 | 2019 | 7 | |
| 11 | 2012 | 5 | |
| 12 | 2018 | 4 | |
| 13 | 2013 | 3 | |
| 14 | 2021 | 2 | |
| 15 | 2015 | 2 | |
| 16 | 2024 | 2 | |
| 17 | 2015 | 2 | |
| 18 | 2020 | 1 | |
| 19 | 2020 | 1 | |
| 20 | 2023 | 1 |
About Greg Hapgood
Greg Hapgood is a scholar working on Pathology and Forensic Medicine, Oncology, Dermatology, Genetics and Neurology, having authored 28 papers that have together received 407 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (20 papers), Cutaneous lymphoproliferative disorders research (5 papers), CNS Lymphoma Diagnosis and Treatment (4 papers), Viral-associated cancers and disorders (3 papers), CAR-T cell therapy research (3 papers), Chronic Lymphocytic Leukemia Research (3 papers), T-cell and Retrovirus Studies (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (216 citations), Internal Medicine (35 citations), Dermatology (66 citations), Oncology (103 citations) and Genetics (36 citations). Greg Hapgood has collaborated with scholars based in Australia, Canada and United Kingdom. Frequent co-authors include Kerry J. Savage, Erica Malan, Sanjeev Chunilal, Diego Villa, Randy D. Gascoyne, David W. Scott, Alina S. Gerrie, Joseph M. Connors, Laurie H. Sehn and Christina Parsons. Their work appears in journals such as Blood, British Journal of Haematology, Blood Advances, Bioinformatics and Thrombosis and Haemostasis.
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.