Erik M. van Mulligen

20.7k citations
107 papers · 1.9k indexed · h-index 29
Topics
Biomedical Text Mining and Ontologies (63 papers)Semantic Web and Ontologies (31 papers)Electronic Health Records Systems (19 papers)

In The Last Decade

Erik M. van Mulligen

104 papers receiving 1.8k citations

Peers

Erik M. van Mulligen
Comparison fields: 5 of 147
  • Molecular Biology 1.2k
  • Artificial Intelligence 986
  • Computational Theory and Mathematics 254
  • Health Information Management 166
  • Information Systems 144
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Countries citing papers authored by Erik M. van Mulligen

Since Specialization
Citations

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

Fields of papers citing papers by Erik M. van Mulligen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik M. van Mulligen. 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 Erik M. van Mulligen. The network helps show where Erik M. van Mulligen may publish in the future.

Co-authorship network of co-authors of Erik M. van Mulligen

This figure shows the co-authorship network connecting the top 25 collaborators of Erik M. van Mulligen. A scholar is included among the top collaborators of Erik M. van Mulligen 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 Erik M. van Mulligen. Erik M. van Mulligen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 3
3 1
4 2
5 6
6 33
7
Drug prioritization using the semantic properties of a knowledge graph
2
8
Erasmus MC at CLEF eHealth 2016: Concept recognition and coding in French texts
10
9 35
10
A fast rule-based approach for biomedical event extraction
37
11
Multilingual semantic resources and parallel corpora in the biomedical domain: The CLEF-ER challenge
3
12
Machine translation of bio-thesauri
1
13 28
14 3
15
TREC 2005 Genomics Track A Concept-Based Approach to Text Categorization.
1
16
Searching for geneRIFs: Concept-Based Query Expansion and Bayes Classification.
12
17
Ambiguity of human gene symbols in LocusLink and MEDLINE: creating an inventory and a disambiguation test collection.
23
18
HEARTVIEW-A Knowledge Base to Support Clinical Research in Cardiology.
1
19
Implementation of a Medical Workstation for Research Support in Cardiology.
4
20
Prototyping for an Integrated Software Environment for Research Support in Cardiology.
1

About Erik M. van Mulligen

Erik M. van Mulligen is a scholar working on Health Information Management, Artificial Intelligence and Health Informatics, having authored 107 papers that have together received 1.9k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (63 papers), Semantic Web and Ontologies (31 papers) and Electronic Health Records Systems (19 papers). The work is most often cited by research in Health Information Management (166 citations), Toxicology (109 citations) and Artificial Intelligence (986 citations). Erik M. van Mulligen has collaborated with scholars based in Netherlands, United Kingdom and Spain. Frequent co-authors include Jan A. Kors, Kang Ning, Barend Mons, Martijn J. Schuemie, Zubair Afzal, Bob J.A. Schijvenaars, Kristina Hettne, Bharat Singh, Rob Jelier and Marc Weeber. Their work appears in journals such as Bioinformatics, PLoS ONE and Scientific Reports.

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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