Paea LePendu

2.7k citations
40 papers · 1.9k · h-index 21

Impact in

Papers in

Paea LePendu

37 papers receiving 1.8k citations

Peers

Paea LePendu
Comparison fields: 5 of 129
  • Toxicology 436
  • Gastroenterology 247
  • Health Information Management 156
  • Computational Theory and Mathematics 274
  • Health Informatics 22
Replace Srinivasan Iyer with:
Srinivasan Iyer United States
Anna Bauer‐Mehren United States
Preciosa M. Coloma Netherlands
Rosa Gini Italy
David Madigan United States
Rae Woong Park South Korea
John R. Horn United States
Dukyong Yoon South Korea
Christian Reich United States
Paul Avillach United States
Paea LePendu relative to Srinivasan Iyer United States Srinivasan Iyer's profile →
Citations per field
00.5×1.5×2.4×
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 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013240
2 2015240
3 2013194
4 2014164
5 2013125
6 2013124
7 201477
8 201273
9 201461
10 201360
11 201158
12 201448
13 201342
14 201437
15 201132
16 200632
17 201432
18
Using temporal patterns in medical records to discern adverse drug events from indications.
201231
19 200631
20 201330

About Paea LePendu

Paea LePendu is a scholar working on Molecular Biology, Artificial Intelligence, Toxicology, Computer Networks and Communications and Cardiology and Cardiovascular Medicine, having authored 40 papers that have together received 1.9k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (21 papers), Semantic Web and Ontologies (11 papers), Pharmacovigilance and Adverse Drug Reactions (10 papers), Computational Drug Discovery Methods (4 papers), Advanced Database Systems and Queries (4 papers), Pharmaceutical studies and practices (4 papers), Bioinformatics and Genomic Networks (4 papers) and Electronic Health Records Systems (3 papers). The work is most often cited by research in Toxicology (436 citations), Gastroenterology (247 citations), Health Information Management (156 citations), Computational Theory and Mathematics (274 citations) and Health Informatics (22 citations). Paea LePendu has collaborated with scholars based in United States, France and Norway. Frequent co-authors include Nigam H. Shah, Srinivasan Iyer, Anna Bauer‐Mehren, Rave Harpaz, John P. Cooke, Yohannes T. Ghebremariam, William DuMouchel, Patrick Ryan, Nicholas J. Leeper and Kenneth Jung. Their work appears in journals such as Journal of the American Medical Informatics Association, PLoS ONE, Clinical Pharmacology & Therapeutics, Circulation and Journal of Biomedical Informatics.

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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