Rave Harpaz
- Toxicology top 0.05%
- Computational Theory and Mathematics top 0.5%
- Molecular Biology top 10%
- Artificial Intelligence top 5%
- Pharmacology top 2%
- Co-authors
- Nigam H. ShahCarol FriedmanWilliam DuMouchelHerbert ChasePaea LePenduPatrick RyanAnna Bauer‐MehrenSantiago Vilar
- Topics
- Pharmacovigilance and Adverse Drug Reactions (26 papers)Computational Drug Discovery Methods (18 papers)Biomedical Text Mining and Ontologies (10 papers)
- Partner nations
- United StatesSpainUnited Kingdom
In The Last Decade
Rave Harpaz
34 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 119
- Toxicology 1.1k
- Computational Theory and Mathematics 884
- Molecular Biology 725
- Artificial Intelligence 322
- Pharmacology 221
Countries citing papers authored by Rave Harpaz
This map shows the geographic impact of Rave Harpaz'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 Rave Harpaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rave Harpaz more than expected).
Fields of papers citing papers by Rave Harpaz
This network shows the impact of papers produced by Rave Harpaz. 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 Rave Harpaz. The network helps show where Rave Harpaz may publish in the future.
Co-authorship network of co-authors of Rave Harpaz
This figure shows the co-authorship network connecting the top 25 collaborators of Rave Harpaz. A scholar is included among the top collaborators of Rave Harpaz 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 Rave Harpaz. Rave Harpaz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | Extracting Positive Mentions of Adverse Drug Reactions from Product Labels using a Machine Learning Centric Approach. | 1 |
| 3 | 28 | |
| 4 | 45 | |
| 5 | 18 | |
| 6 | 32 | |
| 7 | 164 | |
| 8 | 69 | |
| 9 | 33 | |
| 10 | 124 | |
| 11 | 125 | |
| 12 | 240 | |
| 13 | 276 | |
| 14 | 201 | |
| 15 | 22 | |
| 16 | 50 | |
| 17 | 57 | |
| 18 | 140 | |
| 19 | Model-based linear manifold clustering | 1 |
| 20 | 14 |
About Rave Harpaz
Rave Harpaz is a scholar working on Toxicology, Computational Theory and Mathematics and Health Information Management, having authored 34 papers that have together received 2.0k indexed citations. Recurring topics across this work include Pharmacovigilance and Adverse Drug Reactions (26 papers), Computational Drug Discovery Methods (18 papers) and Biomedical Text Mining and Ontologies (10 papers). The work is most often cited by research in Toxicology (1.1k citations), Computational Theory and Mathematics (884 citations) and Health Information Management (130 citations). Rave Harpaz has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Nigam H. Shah, Carol Friedman, William DuMouchel, Herbert Chase, Paea LePendu, Patrick Ryan, Anna Bauer‐Mehren, Santiago Vilar, C Friedman and Raúl Rabadán. Their work appears in journals such as PLoS ONE, BMC Bioinformatics and Pattern Recognition.
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.