John Levander
Impact in
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- COVID-19 epidemiological studies
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- Data-Driven Disease Surveillance
- Influenza Virus Research Studies
Papers in
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- Data-Driven Disease Surveillance 4
- Influenza Virus Research Studies 1
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- Anomaly Detection Techniques and Applications 2
- Bayesian Modeling and Causal Inference 1
- Co-authors
- Gregory F. Cooper (4 shared papers)Michael M. Wagner (7 shared papers)William R. Hogan (7 shared papers)Weng‐Keen Wong (3 shared papers)Denver Dash (2 shared papers)Jeremy U. Espino (1 shared paper)Debasis Dash (1 shared paper)Ronald E. Voorhees (1 shared paper)
- Journals
- Journal of Biomedical Informatics (1 paper)Journal of Biomedical Semantics (1 paper)PubMed (2 papers)Online Journal of Public Health Informatics (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United States
In The Last Decade
John Levander
6 papers receiving 100 citations
Peers
Comparison fields: 5 of 42
- Modeling and Simulation 14
- Epidemiology 72
- Artificial Intelligence 53
- Issues, ethics and legal aspects 1
- Signal Processing 9
Countries citing papers authored by John Levander
This map shows the geographic impact of John Levander'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 John Levander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Levander more than expected).
Fields of papers citing papers by John Levander
This network shows the impact of papers produced by John Levander. 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 John Levander. The network helps show where John Levander may publish in the future.
Co-authors
The 12 scholars most cited alongside John Levander, 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 | 2004 | 70 | |
| 2 | 2011 | 15 | |
| 3 | Use of multiple data streams to conduct Bayesian biologic surveillance. | 2005 | 11 |
| 4 | 2016 | 11 | |
| 5 | 2006 | 3 | |
| 6 | Apollo: giving application developers a single point of access to public health models using structured vocabularies and Web services. | 2013 | 3 |
| 7 | A novel representation of terms related to infectious disease epidemiology for epidemic modeling The Apollo Structured Vocabulary and pre-existing representations | 2014 | 0 |
| 8 | 2024 | 0 |
About John Levander
John Levander is a scholar working on Epidemiology, Artificial Intelligence, Molecular Biology, Information Systems and Management and Computer Networks and Communications, having authored 8 papers that have together received 113 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (4 papers), Scientific Computing and Data Management (2 papers), Biomedical Text Mining and Ontologies (2 papers), Anomaly Detection Techniques and Applications (2 papers), Research Data Management Practices (1 paper), Bayesian Modeling and Causal Inference (1 paper), Influenza Virus Research Studies (1 paper) and Advanced Statistical Process Monitoring (1 paper). The work is most often cited by research in Modeling and Simulation (14 citations), Epidemiology (72 citations), Artificial Intelligence (53 citations), Issues, ethics and legal aspects (1 citation) and Signal Processing (9 citations). John Levander has collaborated with scholars based in United States. Frequent co-authors include Gregory F. Cooper, Michael M. Wagner, William R. Hogan, Weng‐Keen Wong, Denver Dash, Jeremy U. Espino, Debasis Dash, Ronald E. Voorhees, Shawn T. Brown and Fuchiang Tsui. Their work appears in journals such as Journal of Biomedical Informatics, Journal of Biomedical Semantics, PubMed, Online Journal of Public Health Informatics and arXiv (Cornell University).
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.