Davy Weissenbacher

1.2k total citations
42 papers, 676 citations indexed

About

Davy Weissenbacher is a scholar working on Artificial Intelligence, Molecular Biology and Epidemiology. According to data from OpenAlex, Davy Weissenbacher has authored 42 papers receiving a total of 676 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 14 papers in Molecular Biology and 11 papers in Epidemiology. Recurrent topics in Davy Weissenbacher's work include Topic Modeling (13 papers), Biomedical Text Mining and Ontologies (12 papers) and Data-Driven Disease Surveillance (8 papers). Davy Weissenbacher is often cited by papers focused on Topic Modeling (13 papers), Biomedical Text Mining and Ontologies (12 papers) and Data-Driven Disease Surveillance (8 papers). Davy Weissenbacher collaborates with scholars based in United States, United Kingdom and Russia. Davy Weissenbacher's co-authors include Graciela Gonzalez‐Hernandez, Abeed Sarker, Arjun Magge, Karen O’Connor, Ari Z Klein, Michael J. Paul, Matthew Scotch, Ashlynn R. Daughton, Folkert W. Asselbergs and Jason H. Moore and has published in prestigious journals such as Bioinformatics, PLoS ONE and European Heart Journal.

In The Last Decade

Davy Weissenbacher

39 papers receiving 605 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Davy Weissenbacher 342 182 88 85 63 42 676
Arjun Magge 238 0.7× 128 0.7× 68 0.8× 50 0.6× 43 0.7× 24 423
Ai Kawazoe 171 0.5× 165 0.9× 74 0.8× 206 2.4× 9 0.1× 18 447
Ari Z Klein 208 0.6× 59 0.3× 72 0.8× 53 0.6× 33 0.5× 38 474
Guy Divita 406 1.2× 409 2.2× 25 0.3× 70 0.8× 13 0.2× 54 748
Fabio Rinaldi 1.1k 3.3× 869 4.8× 45 0.5× 62 0.7× 15 0.2× 141 1.7k
Allen C. Browne 802 2.3× 785 4.3× 72 0.8× 29 0.3× 18 0.3× 55 1.2k
Ashlynn R. Daughton 117 0.3× 77 0.4× 129 1.5× 120 1.4× 14 0.2× 27 419
Koichi Takeuchi 338 1.0× 230 1.3× 49 0.6× 145 1.7× 3 0.0× 63 604
Herman Tolentino 39 0.1× 54 0.3× 32 0.4× 157 1.8× 9 0.1× 15 296
William Boag 715 2.1× 301 1.7× 30 0.3× 45 0.5× 12 0.2× 12 873

Countries citing papers authored by Davy Weissenbacher

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
2.
Weissenbacher, Davy, Lauren Dutcher, Keith Hamilton, et al.. (2024). Automated Evaluation of Antibiotic Prescribing Guideline Concordance in Pediatric Sinusitis Clinical Notes. 138–153.
3.
O’Connor, Karen, Su Golder, Davy Weissenbacher, et al.. (2024). Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review. Journal of Medical Internet Research. 26. e47923–e47923. 2 indexed citations
4.
Weissenbacher, Davy, Katherine R. Courtright, Andrew Crane‐Droesch, et al.. (2024). Detecting goals of care conversations in clinical notes with active learning. Journal of Biomedical Informatics. 151. 104618–104618. 1 indexed citations
5.
Golder, Su, Karen O’Connor, Davy Weissenbacher, et al.. (2023). Patient-Reported Reasons for Antihypertensive Medication Change: A Quantitative Study Using Social Media. Drug Safety. 47(1). 81–91. 2 indexed citations
6.
Weissenbacher, Davy, Suyu Ge, Ari Z Klein, et al.. (2021). Active neural networks to detect mentions of changes to medication treatment in social media. Journal of the American Medical Informatics Association. 28(12). 2551–2561. 8 indexed citations
7.
Magge, Arjun, Elena Tutubalina, Zulfat Miftahutdinov, et al.. (2021). DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter. Journal of the American Medical Informatics Association. 28(10). 2184–2192. 26 indexed citations
8.
Magge, Arjun, Ari Z Klein, Mohammed Ali Al-Garadi, et al.. (2021). Overview of the Sixth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at NAACL 2021. 21–32. 45 indexed citations
9.
Klein, Ari Z, et al.. (2021). Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set. Journal of Medical Internet Research. 23(1). e25314–e25314. 46 indexed citations
10.
Klein, Ari Z, Ilseyar Alimova, Arjun Magge, et al.. (2020). Overview of the Fifth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2020. HAL (Le Centre pour la Communication Scientifique Directe). 27–36. 32 indexed citations
11.
Wexler, Anna, et al.. (2020). Pregnancy and health in the age of the Internet: A content analysis of online “birth club” forums. PLoS ONE. 15(4). e0230947–e0230947. 34 indexed citations
12.
Weissenbacher, Davy, Abeed Sarker, Ari Z Klein, et al.. (2019). Deep neural networks ensemble for detecting medication mentions in tweets. Journal of the American Medical Informatics Association. 26(12). 1618–1626. 29 indexed citations
13.
Weissenbacher, Davy, Abeed Sarker, Arjun Magge, et al.. (2019). Overview of the Fourth Social Media Mining for Health (SMM4H) Shared Tasks at ACL 2019. 21–30. 70 indexed citations
14.
Klein, Ari Z, Abeed Sarker, Davy Weissenbacher, & Graciela Gonzalez‐Hernandez. (2019). Towards scaling Twitter for digital epidemiology of birth defects. npj Digital Medicine. 2(1). 96–96. 11 indexed citations
15.
Magge, Arjun, Davy Weissenbacher, Abeed Sarker, Matthew Scotch, & Graciela Gonzalez‐Hernandez. (2018). Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature. PubMed. 24. 100–111. 6 indexed citations
16.
Scotch, Matthew, Davy Weissenbacher, Karen O’Connor, et al.. (2018). Incorporating sampling uncertainty in the geospatial assignment of taxa for virus phylogeography. Virus Evolution. 5(1). vey043–vey043. 11 indexed citations
17.
Weissenbacher, Davy, Abeed Sarker, Michael J. Paul, & Graciela Gonzalez‐Hernandez. (2018). Overview of the Third Social Media Mining for Health (SMM4H) Shared Tasks at EMNLP 2018. 13–16. 55 indexed citations
18.
Golder, Su, Stephanie E. Chiuve, Davy Weissenbacher, et al.. (2018). Pharmacoepidemiologic Evaluation of Birth Defects from Health-Related Postings in Social Media During Pregnancy. Drug Safety. 42(3). 389–400. 27 indexed citations
19.
Klein, Ari Z, et al.. (2018). Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter. Journal of Biomedical Informatics. 87. 68–78. 26 indexed citations
20.
Weissenbacher, Davy & Adeline Nazarenko. (2011). Understand the effects of erroneous annotations produced by NLP pipelines, a case study on the pronominal anaphora resolution.. 52. 161–185. 1 indexed citations

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.

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