David Higgins
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Sports Performance and Training
Papers in
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- Artificial Intelligence in Healthcare and Education 3
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- Hepatitis C virus research 3
- Co-authors
- Beverly J. Paigen (7 shared papers)Vince I. Madai (1 shared paper)Fumihiro Sugiyama (1 shared paper)Conrado A. Johns (1 shared paper)Gary A. Churchill (1 shared paper)Haralambos P. Gavras (1 shared paper)Peter M. Kelmenson (2 shared papers)Niall Madden (1 shared paper)
- Journals
- Mammalian Genome (4 papers)Trials (2 papers)Nature Medicine (1 paper)European Journal of Pharmacology (1 paper)JAMA (1 paper)
- Partner nations
- United StatesGermanyIreland
In The Last Decade
David Higgins
23 papers receiving 1.3k citations
David Higgins's Hit Papers
Peers
Comparison fields: 5 of 117
- Health Informatics 318
- Orthopedics and Sports Medicine 87
- Genetics 272
- Immunology 161
- Health Information Management 70
Countries citing papers authored by David Higgins
This map shows the geographic impact of David Higgins'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 David Higgins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Higgins more than expected).
Fields of papers citing papers by David Higgins
This network shows the impact of papers produced by David Higgins. 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 David Higgins. The network helps show where David Higgins may publish in the future.
Co-authors
The 25 scholars most cited alongside David Higgins, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI Hit paper breakdown → | 2022 | 410 |
| 2 | 2005 | 242 | |
| 3 | 2001 | 174 | |
| 4 | 2007 | 124 | |
| 5 | 2020 | 85 | |
| 6 | 2022 | 53 | |
| 7 | 2016 | 42 | |
| 8 | 2002 | 36 | |
| 9 | 2004 | 31 | |
| 10 | 1998 | 26 | |
| 11 | 2014 | 25 | |
| 12 | 2001 | 23 | |
| 13 | 2023 | 23 | |
| 14 | 2014 | 20 | |
| 15 | 2015 | 16 | |
| 16 | 2022 | 7 | |
| 17 | 1997 | 6 | |
| 18 | 2009 | 6 | |
| 19 | 2025 | 6 | |
| 20 | 2023 | 3 |
About David Higgins
David Higgins is a scholar working on Health Informatics, Hepatology, Genetics, Cellular and Molecular Neuroscience and Immunology, having authored 23 papers that have together received 1.4k indexed citations. Recurring topics across this work include Genetic Mapping and Diversity in Plants and Animals (5 papers), Artificial Intelligence in Healthcare and Education (3 papers), Hepatitis C virus research (3 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Pregnancy and preeclampsia studies (2 papers), Genetic Associations and Epidemiology (2 papers) and Cardiovascular and exercise physiology (1 paper). The work is most often cited by research in Health Informatics (318 citations), Orthopedics and Sports Medicine (87 citations), Genetics (272 citations), Immunology (161 citations) and Health Information Management (70 citations). David Higgins has collaborated with scholars based in United States, Germany and Ireland. Frequent co-authors include Beverly J. Paigen, Vince I. Madai, Fumihiro Sugiyama, Conrado A. Johns, Gary A. Churchill, Haralambos P. Gavras, Peter M. Kelmenson, Niall Madden, Jochen Einbeck and Ulf dé Fairé. Their work appears in journals such as Mammalian Genome, Trials, Nature Medicine, European Journal of Pharmacology and JAMA.
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.