Paul Hanbury
- Artificial Intelligence top 2%
- Molecular Biology
- Health Information Management top 1%
- Epidemiology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Gregory F. CooperWendy W. ChapmanWill BridewellBruce G. BuchananB. G. BuchananBrian E. ChapmanMichael M. WagnerLee H. Harrison
- Topics
- Biomedical Text Mining and Ontologies (2 papers)Topic Modeling (2 papers)Electronic Health Records Systems (2 papers)
- Journals
- Journal of the American Medical Informatics AssociationSleep MedicineCanadian Journal of Chemistry
- Partner nations
- United StatesCanada
In The Last Decade
Paul Hanbury
7 papers receiving 900 citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 686
- Molecular Biology 618
- Health Information Management 141
- Epidemiology 67
- Radiology, Nuclear Medicine and Imaging 58
Countries citing papers authored by Paul Hanbury
This map shows the geographic impact of Paul Hanbury'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 Paul Hanbury with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Hanbury more than expected).
Fields of papers citing papers by Paul Hanbury
This network shows the impact of papers produced by Paul Hanbury. 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 Paul Hanbury. The network helps show where Paul Hanbury may publish in the future.
Co-authorship network of co-authors of Paul Hanbury
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Hanbury. A scholar is included among the top collaborators of Paul Hanbury based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul Hanbury. Paul Hanbury is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 37 | |
| 3 | Detecting adverse drug events in discharge summaries using variations on the simple Bayes model. | 13 |
| 4 | Creating a Software Tool for the Clinical Researcher -- the IPS System | 2 |
| 5 | A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summariesbreakdown → | 779 |
| 6 | Evaluation of negation phrases in narrative clinical reports. | 127 |
| 7 | 6 |
About Paul Hanbury
Paul Hanbury is a scholar working on Health Information Management, Toxicology and Geriatrics and Gerontology, having authored 7 papers that have together received 965 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (2 papers), Topic Modeling (2 papers) and Electronic Health Records Systems (2 papers). The work is most often cited by research in Health Information Management (141 citations), Artificial Intelligence (686 citations) and Health Informatics (25 citations). Paul Hanbury has collaborated with scholars based in United States and Canada. Frequent co-authors include Gregory F. Cooper, Wendy W. Chapman, Will Bridewell, Bruce G. Buchanan, B. G. Buchanan, Brian E. Chapman, Michael M. Wagner, Lee H. Harrison, Melissa Saul and Shyam Visweswaran. Their work appears in journals such as Journal of the American Medical Informatics Association, Sleep Medicine and Canadian Journal of Chemistry.
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.