Sujan Perera
Impact in
- Toxicology top 5%
- Pharmacovigilance and Adverse Drug Reactions
Papers in
-
- Topic Modeling 4
- Semantic Web and Ontologies 3
- Natural Language Processing Techniques 1
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- Biomedical Text Mining and Ontologies 4
- Co-authors
- Amit Sheth (6 shared papers)Raminta Daniulaityte (1 shared paper)Lu Chen (1 shared paper)Delroy Cameron (1 shared paper)Robert G. Carlson (1 shared paper)Rüssel S. Falck (1 shared paper)Krishnaprasad Thirunarayan (4 shared papers)Zoë Hudson (1 shared paper)
- Journals
- IEEE Journal of Biomedical and Health Informatics (1 paper)Drug Safety (1 paper)Drug and Alcohol Dependence (1 paper)Pharmaceutical Medicine (2 papers)Journal of Bioresource Management (2 papers)
- Partner nations
- United StatesSwitzerlandSri Lanka
In The Last Decade
Sujan Perera
10 papers receiving 233 citations
Peers
Comparison fields: 5 of 75
- Toxicology 73
- Health Informatics 11
- Emergency Medicine 71
- Health Information Management 18
- Pharmacology 33
Countries citing papers authored by Sujan Perera
This map shows the geographic impact of Sujan Perera'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 Sujan Perera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujan Perera more than expected).
Fields of papers citing papers by Sujan Perera
This network shows the impact of papers produced by Sujan Perera. 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 Sujan Perera. The network helps show where Sujan Perera may publish in the future.
Co-authors
The 17 scholars most cited alongside Sujan Perera, 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 | 2012 | 106 | |
| 2 | 2019 | 32 | |
| 3 | 2018 | 32 | |
| 4 | 2018 | 22 | |
| 5 | 2013 | 16 | |
| 6 | 2013 | 13 | |
| 7 | 2012 | 9 | |
| 8 | 2016 | 6 | |
| 9 | 2015 | 5 | |
| 10 | 2017 | 5 |
About Sujan Perera
Sujan Perera is a scholar working on Artificial Intelligence, Molecular Biology, Toxicology, Management Science and Operations Research and Public Health, Environmental and Occupational Health, having authored 10 papers that have together received 246 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Topic Modeling (4 papers), Pharmacovigilance and Adverse Drug Reactions (3 papers), Semantic Web and Ontologies (3 papers), Data Quality and Management (3 papers), Pharmaceutical Practices and Patient Outcomes (1 paper), Poisoning and overdose treatments (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Toxicology (73 citations), Health Informatics (11 citations), Emergency Medicine (71 citations), Health Information Management (18 citations) and Pharmacology (33 citations). Sujan Perera has collaborated with scholars based in United States, Switzerland and Sri Lanka. Frequent co-authors include Amit Sheth, Raminta Daniulaityte, Lu Chen, Delroy Cameron, Robert G. Carlson, Rüssel S. Falck, Krishnaprasad Thirunarayan, Zoë Hudson, C. R. Ramakrishnan and Jennifer Fine. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Drug Safety, Drug and Alcohol Dependence, Pharmaceutical Medicine and Journal of Bioresource Management.
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.