Scott Halgrim
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Electronic Health Records Systems
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 3
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- Electronic Health Records Systems 1
- Co-authors
- David Carrell (6 shared papers)Cheryl Clark (3 shared papers)Diana S.M. Buist (2 shared papers)Wendy W. Chapman (2 shared papers)Jessica Chubak (2 shared papers)Guergana Savova (2 shared papers)Sunghwan Sohn (2 shared papers)Christopher G. Chute (2 shared papers)
- Journals
- American Journal of Epidemiology (2 papers)Journal of Biomedical Semantics (1 paper)PLoS ONE (1 paper)Journal of the American Medical Informatics Association (1 paper)Clinical Medicine & Research (1 paper)
- Partner nations
- United States
In The Last Decade
Scott Halgrim
11 papers receiving 393 citations
Peers
Comparison fields: 5 of 57
- Health Informatics 16
- Health Information Management 36
- Artificial Intelligence 162
- Toxicology 13
- Computer Science Applications 16
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 | 136 | |
| 2 | 2014 | 91 | |
| 3 | 2014 | 84 | |
| 4 | Preliminary Experiments with Amazon's Mechanical Turk for Annotating Medical Named Entities | 2010 | 28 |
| 5 | 2016 | 20 | |
| 6 | 2011 | 16 | |
| 7 | Extracting Medication Information from Discharge Summaries | 2010 | 13 |
| 8 | 2013 | 9 | |
| 9 | 2014 | 3 | |
| 10 | 2013 | 1 | |
| 11 | 2015 | 1 |
About Scott Halgrim
Scott Halgrim is a scholar working on Artificial Intelligence, Health Information Management, Computer Science Applications, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 11 papers that have together received 402 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers), Lung Cancer Diagnosis and Treatment (2 papers), Global Cancer Incidence and Screening (1 paper), Ethics in Clinical Research (1 paper), Electronic Health Records Systems (1 paper) and Mobile Crowdsensing and Crowdsourcing (1 paper). The work is most often cited by research in Health Informatics (16 citations), Health Information Management (36 citations), Artificial Intelligence (162 citations), Toxicology (13 citations) and Computer Science Applications (16 citations). Scott Halgrim has collaborated with scholars based in United States. Frequent co-authors include David Carrell, Cheryl Clark, Diana S.M. Buist, Wendy W. Chapman, Jessica Chubak, Guergana Savova, Sunghwan Sohn, Christopher G. Chute, Sean Patrick Murphy and Hongfang Liu. Their work appears in journals such as American Journal of Epidemiology, Journal of Biomedical Semantics, PLoS ONE, Journal of the American Medical Informatics Association and Clinical Medicine & Research.
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.