Andrew J. King
- Co-authors
- Gregory F. CooperHarry HochheiserGilles ClermontMiloš HauskrechtShyam VisweswaranDean F. SittigJeremy M. KahnJohn Willan
- Topics
- Electronic Health Records Systems (10 papers)Machine Learning in Healthcare (7 papers)Biomedical Text Mining and Ontologies (5 papers)
- Journals
- Journal of the American Society of NephrologyJournal of Medical Internet ResearchBritish Journal of Haematology
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Andrew J. King
18 papers receiving 168 citations
Peers
Comparison fields: 5 of 64
- Health Information Management 61
- Artificial Intelligence 45
- Surgery 33
- Oncology 24
- Epidemiology 23
Countries citing papers authored by Andrew J. King
This map shows the geographic impact of Andrew J. King'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 Andrew J. King with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew J. King more than expected).
Fields of papers citing papers by Andrew J. King
This network shows the impact of papers produced by Andrew J. King. 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 Andrew J. King. The network helps show where Andrew J. King may publish in the future.
Co-authorship network of co-authors of Andrew J. King
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. King. A scholar is included among the top collaborators of Andrew J. King 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 Andrew J. King. Andrew J. King is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 0 | |
| 7 | 8 | |
| 8 | 13 | |
| 9 | 16 | |
| 10 | 7 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 5 | |
| 14 | 16 | |
| 15 | 29 | |
| 16 | 20 | |
| 17 | Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System. | 13 |
| 18 | Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR. | 14 |
| 19 | 3 | |
| 20 | Development and Preliminary Evaluation of a Prototype of a Learning Electronic Medical Record System. | 9 |
About Andrew J. King
Andrew J. King is a scholar working on Health Information Management, Health Informatics and Family Practice, having authored 20 papers that have together received 171 indexed citations. Recurring topics across this work include Electronic Health Records Systems (10 papers), Machine Learning in Healthcare (7 papers) and Biomedical Text Mining and Ontologies (5 papers). The work is most often cited by research in Health Informatics (21 citations), Health Information Management (61 citations) and Family Practice (8 citations). Andrew J. King has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Gregory F. Cooper, Harry Hochheiser, Gilles Clermont, Miloš Hauskrecht, Shyam Visweswaran, Dean F. Sittig, Jeremy M. Kahn, John Willan, Graham P. Collins and Sue Pavord. Their work appears in journals such as Journal of the American Society of Nephrology, Journal of Medical Internet Research and British Journal of Haematology.
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.