Emily Pfaff
Impact in
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- Electronic Health Records Systems
- Health Informatics top 10%
Papers in
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- Machine Learning in Healthcare 11
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- Artificial Intelligence in Healthcare 6
- Electronic Health Records Systems 5
- Co-authors
- Christopher G. Chute (20 shared papers)Stanley C. Ahalt (7 shared papers)Karamarie Fecho (7 shared papers)Melissa Haendel (16 shared papers)Johanna Loomba (7 shared papers)Richard A. Moffitt (11 shared papers)Ashok Krishnamurthy (4 shared papers)Elaine Hill (4 shared papers)
- Journals
- Journal of the American Medical Informatics Association (7 papers)Journal of Biomedical Informatics (3 papers)PLoS Medicine (2 papers)Clinical Infectious Diseases (1 paper)Diabetes (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Emily Pfaff
48 papers receiving 626 citations
Emily Pfaff's Hit Papers
Peers
Comparison fields: 5 of 97
- Health Information Management 105
- Health Informatics 14
- Neurology 123
- Critical Care and Intensive Care Medicine 37
- Health, Toxicology and Mutagenesis 67
Countries citing papers authored by Emily Pfaff
This map shows the geographic impact of Emily Pfaff'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 Emily Pfaff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily Pfaff more than expected).
Fields of papers citing papers by Emily Pfaff
This network shows the impact of papers produced by Emily Pfaff. 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 Emily Pfaff. The network helps show where Emily Pfaff may publish in the future.
Co-authors
The 25 scholars most cited alongside Emily Pfaff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Coding long COVID: characterizing a new disease through an ICD-10 lens Hit paper breakdown → | 2023 | 84 |
| 2 | 2014 | 51 | |
| 3 | 2018 | 47 | |
| 4 | 2019 | 43 | |
| 5 | 2015 | 41 | |
| 6 | 2020 | 31 | |
| 7 | 2013 | 30 | |
| 8 | 2016 | 29 | |
| 9 | 2020 | 28 | |
| 10 | 2023 | 25 | |
| 11 | 2022 | 22 | |
| 12 | 2024 | 18 | |
| 13 | 2022 | 17 | |
| 14 | 2019 | 17 | |
| 15 | 2019 | 15 | |
| 16 | 2019 | 13 | |
| 17 | 2020 | 12 | |
| 18 | 2021 | 11 | |
| 19 | 2022 | 10 | |
| 20 | 2021 | 9 |
About Emily Pfaff
Emily Pfaff is a scholar working on Artificial Intelligence, Health Information Management, Neurology, Infectious Diseases and Molecular Biology, having authored 50 papers that have together received 638 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (11 papers), Long-Term Effects of COVID-19 (10 papers), COVID-19 Clinical Research Studies (9 papers), Biomedical Text Mining and Ontologies (8 papers), Artificial Intelligence in Healthcare (6 papers), Electronic Health Records Systems (5 papers), Diabetes Management and Research (4 papers) and Air Quality and Health Impacts (4 papers). The work is most often cited by research in Health Information Management (105 citations), Health Informatics (14 citations), Neurology (123 citations), Critical Care and Intensive Care Medicine (37 citations) and Health, Toxicology and Mutagenesis (67 citations). Emily Pfaff has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Christopher G. Chute, Stanley C. Ahalt, Karamarie Fecho, Melissa Haendel, Johanna Loomba, Richard A. Moffitt, Ashok Krishnamurthy, Elaine Hill, Robert L. Bradford and Hao Xu. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, PLoS Medicine, Clinical Infectious Diseases and Diabetes.
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.