Casey S. Husser
- Molecular Biology
- Artificial Intelligence top 10%
- Health Information Management top 2%
- Public Health, Environmental and Occupational Health
- Language and Linguistics top 10%
- Co-authors
- Steven H. BrownPeter L. ElkinBrent A. BauerDietlind L. Wahner‐RoedlerS. Trent RosenbloomTed SperoffLarry BergstromWilliam Carruth
- Topics
- Biomedical Text Mining and Ontologies (6 papers)Semantic Web and Ontologies (2 papers)Clinical practice guidelines implementation (1 paper)
- Partner nations
- United StatesVietnamIsrael
In The Last Decade
Casey S. Husser
8 papers receiving 328 citations
Peers
Comparison fields: 5 of 69
- Molecular Biology 237
- Artificial Intelligence 189
- Health Information Management 81
- Public Health, Environmental and Occupational Health 28
- Language and Linguistics 26
Countries citing papers authored by Casey S. Husser
This map shows the geographic impact of Casey S. Husser'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 Casey S. Husser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Casey S. Husser more than expected).
Fields of papers citing papers by Casey S. Husser
This network shows the impact of papers produced by Casey S. Husser. 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 Casey S. Husser. The network helps show where Casey S. Husser may publish in the future.
Co-authorship network of co-authors of Casey S. Husser
This figure shows the co-authorship network connecting the top 25 collaborators of Casey S. Husser. A scholar is included among the top collaborators of Casey S. Husser 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 Casey S. Husser. Casey S. Husser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Using SNOMED CT as a reference terminology to cross map two highly pre-coordinated classification systems. | 8 |
| 2 | 145 | |
| 3 | SNOMED CT: utility for a general medical evaluation template. | 17 |
| 4 | 8 | |
| 5 | 102 | |
| 6 | 1 | |
| 7 | VA National Drug File Reference Terminology: a cross-institutional content coverage study. | 68 |
| 8 | 3 |
About Casey S. Husser
Casey S. Husser is a scholar working on Health Information Management, Critical Care and Intensive Care Medicine and Emergency Medicine, having authored 8 papers that have together received 352 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (6 papers), Semantic Web and Ontologies (2 papers) and Clinical practice guidelines implementation (1 paper). The work is most often cited by research in Health Information Management (81 citations), Medical Terminology (3 citations) and Artificial Intelligence (189 citations). Casey S. Husser has collaborated with scholars based in United States, Vietnam and Israel. Frequent co-authors include Steven H. Brown, Peter L. Elkin, Brent A. Bauer, Dietlind L. Wahner‐Roedler, S. Trent Rosenbloom, Ted Speroff, Larry Bergstrom, William Carruth, John S. Carter and Mark S. Erlbaum. Their work appears in journals such as Anesthesiology, Mayo Clinic Proceedings and BMC Medical Informatics and Decision Making.
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.