Megan Kaiser
Impact in
-
- Electronic Health Records Systems
- Health Informatics top 10%
Papers in
-
- Topic Modeling 3
- Natural Language Processing Techniques 2
- Machine Learning in Healthcare 1
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- Biomedical Text Mining and Ontologies 2
- Co-authors
- Imre Solti (13 shared papers)Todd Lingren (13 shared papers)Louise Deléger (10 shared papers)Laura Stoutenborough (10 shared papers)Qi Li (7 shared papers)Haijun Zhai (8 shared papers)Yizhao Ni (5 shared papers)Keith Marsolo (3 shared papers)
- Journals
- Journal of the American Medical Informatics Association (4 papers)BMC Medical Informatics and Decision Making (3 papers)Journal of Biomedical Informatics (2 papers)Journal of Medical Internet Research (1 paper)PubMed (2 papers)
- Partner nations
- United StatesHong Kong
In The Last Decade
Megan Kaiser
14 papers receiving 473 citations
Peers
Comparison fields: 5 of 81
- Health Information Management 66
- Health Informatics 15
- Toxicology 21
- Computer Science Applications 28
- Artificial Intelligence 160
Countries citing papers authored by Megan Kaiser
This map shows the geographic impact of Megan Kaiser'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 Megan Kaiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Megan Kaiser more than expected).
Fields of papers citing papers by Megan Kaiser
This network shows the impact of papers produced by Megan Kaiser. 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 Megan Kaiser. The network helps show where Megan Kaiser may publish in the future.
Co-authors
The 25 scholars most cited alongside Megan Kaiser, 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 | 2015 | 90 | |
| 2 | 2012 | 60 | |
| 3 | 2013 | 59 | |
| 4 | Building gold standard corpora for medical natural language processing tasks. | 2012 | 55 |
| 5 | 2013 | 52 | |
| 6 | 2014 | 43 | |
| 7 | 2015 | 28 | |
| 8 | 2015 | 27 | |
| 9 | 2013 | 26 | |
| 10 | 2014 | 23 | |
| 11 | 2012 | 18 | |
| 12 | 2012 | 2 | |
| 13 | [Problems of Viennese drinking water]. | 1952 | 2 |
| 14 | 2012 | 1 |
About Megan Kaiser
Megan Kaiser is a scholar working on Artificial Intelligence, Molecular Biology, Communication, Emergency Medical Services and Computer Science Applications, having authored 14 papers that have together received 486 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Biomedical Text Mining and Ontologies (2 papers), Natural Language Processing Techniques (2 papers), Wikis in Education and Collaboration (1 paper), Patient Safety and Medication Errors (1 paper), Machine Learning in Healthcare (1 paper) and Mobile Crowdsensing and Crowdsourcing (1 paper). The work is most often cited by research in Health Information Management (66 citations), Health Informatics (15 citations), Toxicology (21 citations), Computer Science Applications (28 citations) and Artificial Intelligence (160 citations). Megan Kaiser has collaborated with scholars based in United States and Hong Kong. Frequent co-authors include Imre Solti, Todd Lingren, Louise Deléger, Laura Stoutenborough, Qi Li, Haijun Zhai, Yizhao Ni, Keith Marsolo, John P. Perentesis and Isaac S. Kohane. Their work appears in journals such as Journal of the American Medical Informatics Association, BMC Medical Informatics and Decision Making, Journal of Biomedical Informatics, Journal of Medical Internet Research 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.