Paea LePendu

2.7k citations
45 papers · 2.1k · h-index 22

Impact in

Papers in

Paea LePendu

42 papers receiving 2.0k citations

Peers

Paea LePendu
Comparison fields: 5 of 135
  • Toxicology 381
  • Gastroenterology 226
  • Health Information Management 133
  • Artificial Intelligence 518
  • Health Informatics 19
Replace Srinivasan Iyer with:
Srinivasan Iyer United States
Anna Bauer‐Mehren United States
Rae Woong Park South Korea
David Madigan United States
Preciosa M. Coloma Netherlands
Christian Reich United States
Jon Duke United States
Peter Bjødstrup Jensen Denmark
Dukyong Yoon South Korea
Carol Friedman United States
Paea LePendu relative to Srinivasan Iyer United States Srinivasan Iyer's profile →
Citations per field
00.5×1.5×2.5×
Srinivasan Iyer · 1×
Citations per year

Countries citing papers authored by Paea LePendu

Since Specialization
Citations

This map shows the geographic impact of Paea LePendu'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 Paea LePendu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paea LePendu more than expected).

Fields of papers citing papers by Paea LePendu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paea LePendu. 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 Paea LePendu. The network helps show where Paea LePendu may publish in the future.

Co-authors

The 25 scholars most cited alongside Paea LePendu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Paea LePendu Line = papers co-authored together Paea LePendu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015252
2 2013243
3 2013197
4 2014185
5 2013136
6 2013133
7 201488
8 201278
9 201172
10 201365
11 201463
12 201450
13 201348
14 200643
15 201440
16 200639
17 201137
18 201433
19
Using temporal patterns in medical records to discern adverse drug events from indications.
201233
20 200732

About Paea LePendu

Paea LePendu is a scholar working on Molecular Biology, Artificial Intelligence, Toxicology, Computer Networks and Communications and Information Systems, having authored 45 papers that have together received 2.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (21 papers), Semantic Web and Ontologies (15 papers), Pharmacovigilance and Adverse Drug Reactions (10 papers), Advanced Database Systems and Queries (6 papers), Service-Oriented Architecture and Web Services (5 papers), Bioinformatics and Genomic Networks (4 papers), Pharmaceutical studies and practices (4 papers) and Data Quality and Management (3 papers). The work is most often cited by research in Toxicology (381 citations), Gastroenterology (226 citations), Health Information Management (133 citations), Artificial Intelligence (518 citations) and Health Informatics (19 citations). Paea LePendu has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Nigam H. Shah, Srinivasan Iyer, Anna Bauer‐Mehren, Rave Harpaz, John P. Cooke, Yohannes T. Ghebremariam, Dejing Dou, William DuMouchel, Nicholas J. Leeper and Patrick Ryan. Their work appears in journals such as Journal of the American Medical Informatics Association, PLoS ONE, Circulation, Journal of Biomedical Informatics and Clinical Pharmacology & Therapeutics.

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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