Scott Halgrim
Impact in
- Health Informatics top 10%
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- Electronic Health Records Systems
Papers in
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- Topic Modeling 5
- Natural Language Processing Techniques 4
- Text Readability and Simplification 1
- Advanced Text Analysis Techniques 1
- AI in cancer detection 1
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- Biomedical Text Mining and Ontologies 4
- Co-authors
- David Carrell (5 shared papers)Cheryl Clark (4 shared papers)Diana S.M. Buist (2 shared papers)Guergana Savova (1 shared paper)Jessica Chubak (1 shared paper)Wendy W. Chapman (1 shared paper)Christopher G. Chute (2 shared papers)Sunghwan Sohn (2 shared papers)
- Journals
- Journal of the American Medical Informatics Association (1 paper)PLoS ONE (1 paper)Journal of Biomedical Semantics (1 paper)American Journal of Epidemiology (1 paper)PubMed (1 paper)
- Partner nations
- United States
In The Last Decade
Scott Halgrim
10 papers receiving 353 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 12
- Health Information Management 33
- Artificial Intelligence 140
- Toxicology 10
- Computer Science Applications 13
Countries citing papers authored by Scott Halgrim
This map shows the geographic impact of Scott Halgrim'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 Scott Halgrim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Halgrim more than expected).
Fields of papers citing papers by Scott Halgrim
This network shows the impact of papers produced by Scott Halgrim. 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 Scott Halgrim. The network helps show where Scott Halgrim may publish in the future.
Co-authors
The 25 scholars most cited alongside Scott Halgrim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 133 | |
| 2 | 2014 | 77 | |
| 3 | 2014 | 77 | |
| 4 | Preliminary Experiments with Amazon's Mechanical Turk for Annotating Medical Named Entities | 2010 | 22 |
| 5 | 2016 | 20 | |
| 6 | 2011 | 15 | |
| 7 | Extracting Medication Information from Discharge Summaries | 2010 | 9 |
| 8 | 2013 | 8 | |
| 9 | 2015 | 1 | |
| 10 | Negation's Not Solved: Reconsidering Negation Annotation and Evaluation. | 2013 | 1 |
About Scott Halgrim
Scott Halgrim is a scholar working on Artificial Intelligence, Molecular Biology, Pulmonary and Respiratory Medicine, Computer Science Applications and Infectious Diseases, having authored 10 papers that have together received 363 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Biomedical Text Mining and Ontologies (4 papers), Natural Language Processing Techniques (4 papers), Lung Cancer Diagnosis and Treatment (2 papers), Text Readability and Simplification (1 paper), Mobile Crowdsensing and Crowdsourcing (1 paper), Advanced Text Analysis Techniques (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Health Informatics (12 citations), Health Information Management (33 citations), Artificial Intelligence (140 citations), Toxicology (10 citations) and Computer Science Applications (13 citations). Scott Halgrim has collaborated with scholars based in United States. Frequent co-authors include David Carrell, Cheryl Clark, Diana S.M. Buist, Guergana Savova, Jessica Chubak, Wendy W. Chapman, Christopher G. Chute, Sunghwan Sohn, Seán Murphy and Hongfang Liu. Their work appears in journals such as Journal of the American Medical Informatics Association, PLoS ONE, Journal of Biomedical Semantics, American Journal of Epidemiology and PubMed.
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.