Justin Bohn
Impact in
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- Pharmacovigilance and Adverse Drug Reactions
Papers in ⓘ
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- Pharmacovigilance and Adverse Drug Reactions 2
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- Statistical Methods and Inference 3
- Advanced Causal Inference Techniques 3
- Statistical Methods and Bayesian Inference 2
- Co-authors
- Rishi Desai (5 shared papers)Zhongmin Zhou (1 shared paper)Maria Siemionow (1 shared paper)Lin Yang (1 shared paper)Unni M. Chandrasekharan (1 shared paper)Paul E. DiCorleto (1 shared paper)Joshua J. Gagne (5 shared papers)Earl Poptic (1 shared paper)
- Journals
- American Journal of Epidemiology (3 papers)Blood (2 papers)Multiple Sclerosis and Related Disorders (1 paper)PLoS Medicine (1 paper)Journal of Affective Disorders (1 paper)
- Partner nations
- United StatesSouth KoreaItaly
In The Last Decade
Justin Bohn
20 papers receiving 270 citations
Peers
Comparison fields: 5 of 88
- Family Practice 11
- Toxicology 15
- Economics and Econometrics 76
- Pharmacology 24
- Immunology and Allergy 15
Countries citing papers authored by Justin Bohn
This map shows the geographic impact of Justin Bohn'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 Justin Bohn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Bohn more than expected).
Fields of papers citing papers by Justin Bohn
This network shows the impact of papers produced by Justin Bohn. 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 Justin Bohn. The network helps show where Justin Bohn may publish in the future.
Co-authors
The 25 scholars most cited alongside Justin Bohn, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 79 | |
| 2 | 2019 | 49 | |
| 3 | 2018 | 25 | |
| 4 | 2012 | 18 | |
| 5 | 2014 | 18 | |
| 6 | 2015 | 16 | |
| 7 | 2021 | 13 | |
| 8 | 2022 | 13 | |
| 9 | 2018 | 8 | |
| 10 | 2020 | 8 | |
| 11 | 2012 | 8 | |
| 12 | 2018 | 6 | |
| 13 | 2022 | 4 | |
| 14 | 2019 | 3 | |
| 15 | 2021 | 2 | |
| 16 | 2022 | 2 | |
| 17 | 2016 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2021 | 1 | |
| 20 | 2020 | 1 |
About Justin Bohn
Justin Bohn is a scholar working on Toxicology, Statistics and Probability, Pharmacology, Internal Medicine and Economics and Econometrics, having authored 21 papers that have together received 276 indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (6 papers), Pharmaceutical industry and healthcare (4 papers), Pharmaceutical Economics and Policy (4 papers), Statistical Methods and Inference (3 papers), Advanced Causal Inference Techniques (3 papers), Pharmacovigilance and Adverse Drug Reactions (2 papers), Statistical Methods and Bayesian Inference (2 papers) and Atrial Fibrillation Management and Outcomes (2 papers). The work is most often cited by research in Family Practice (11 citations), Toxicology (15 citations), Economics and Econometrics (76 citations), Pharmacology (24 citations) and Immunology and Allergy (15 citations). Justin Bohn has collaborated with scholars based in United States, South Korea and Italy. Frequent co-authors include Rishi Desai, Zhongmin Zhou, Maria Siemionow, Lin Yang, Unni M. Chandrasekharan, Paul E. DiCorleto, Joshua J. Gagne, Earl Poptic, Philip H. Howe and Kağan Özer. Their work appears in journals such as American Journal of Epidemiology, Blood, Multiple Sclerosis and Related Disorders, PLoS Medicine and Journal of Affective Disorders.
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.