Davy Weissenbacher
- Artificial Intelligence top 5%
- Molecular Biology
- Sociology and Political Science
- Epidemiology
- Toxicology top 5%
- Co-authors
- Graciela Gonzalez‐HernandezAbeed SarkerArjun MaggeKaren O’ConnorAri Z KleinMichael J. PaulMatthew ScotchJason H. Moore
- Topics
- Topic Modeling (13 papers)Biomedical Text Mining and Ontologies (12 papers)Data-Driven Disease Surveillance (8 papers)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Davy Weissenbacher
39 papers receiving 605 citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 342
- Molecular Biology 182
- Sociology and Political Science 88
- Epidemiology 85
- Toxicology 63
Countries citing papers authored by Davy Weissenbacher
This map shows the geographic impact of Davy Weissenbacher'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 Davy Weissenbacher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davy Weissenbacher more than expected).
Fields of papers citing papers by Davy Weissenbacher
This network shows the impact of papers produced by Davy Weissenbacher. 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 Davy Weissenbacher. The network helps show where Davy Weissenbacher may publish in the future.
Co-authorship network of co-authors of Davy Weissenbacher
This figure shows the co-authorship network connecting the top 25 collaborators of Davy Weissenbacher. A scholar is included among the top collaborators of Davy Weissenbacher based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Davy Weissenbacher. Davy Weissenbacher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 26 | |
| 7 | 8 | |
| 8 | 45 | |
| 9 | 46 | |
| 10 | Overview of the Fifth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2020 | 32 |
| 11 | 34 | |
| 12 | 17 | |
| 13 | 29 | |
| 14 | 11 | |
| 15 | 70 | |
| 16 | 6 | |
| 17 | 11 | |
| 18 | 55 | |
| 19 | 26 | |
| 20 | Understand the effects of erroneous annotations produced by NLP pipelines, a case study on the pronominal anaphora resolution. | 1 |
About Davy Weissenbacher
Davy Weissenbacher is a scholar working on Family Practice, Health Information Management and Health Informatics, having authored 42 papers that have together received 676 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Biomedical Text Mining and Ontologies (12 papers) and Data-Driven Disease Surveillance (8 papers). The work is most often cited by research in Health Informatics (34 citations), Toxicology (63 citations) and Artificial Intelligence (342 citations). Davy Weissenbacher has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Graciela Gonzalez‐Hernandez, Abeed Sarker, Arjun Magge, Karen O’Connor, Ari Z Klein, Michael J. Paul, Matthew Scotch, Jason H. Moore, Ashlynn R. Daughton and Folkert W. Asselbergs. Their work appears in journals such as Bioinformatics, PLoS ONE and European Heart Journal.
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.