David Luis Wiegandt

690 citations
6 papers · 413 indexed · 1 hit paper · h-index 5
Topics
Biomedical Text Mining and Ontologies (4 papers)Cancer Genomics and Diagnostics (2 papers)Genomics and Rare Diseases (2 papers)
Partner nations
GermanyUnited States

In The Last Decade

David Luis Wiegandt

6 papers receiving 393 citations

Hit Papers

Deep learning with word embeddings improves biomedical na...20172026202020232017100200300

Peers

David Luis Wiegandt
Comparison fields: 5 of 71
  • Artificial Intelligence 295
  • Molecular Biology 290
  • Computational Theory and Mathematics 21
  • Genetics 21
  • Cancer Research 17
Replace Maryam Habibi with:
Maryam Habibi Switzerland
Mariana Neves Germany
Maulik R. Kamdar United States
Heinz‐Theodor Mevissen Germany
Hung Yu Kao Taiwan
Zhiyong Lu United States
Harald Kirsch United Kingdom
Jurica Ševa Germany
Bryan Rink United States
Jasmin Šarić Germany
David Luis Wiegandt relative to Maryam Habibi Switzerland Maryam Habibi's profile →
Citations per field
00.5×2.8×
Maryam Habibi · 1×
Citations per year

Countries citing papers authored by David Luis Wiegandt

Since Specialization
Citations

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

Fields of papers citing papers by David Luis Wiegandt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Luis Wiegandt. 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 David Luis Wiegandt. The network helps show where David Luis Wiegandt may publish in the future.

Co-authorship network of co-authors of David Luis Wiegandt

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

All Works

6 of 6 papers shown
#WorkIndexed citations
1 4
2 7
3 15
4
Deep learning with word embeddings improves biomedical named entity recognitionbreakdown →
356
5 10
6 21

About David Luis Wiegandt

David Luis Wiegandt is a scholar working on Management of Technology and Innovation, Cancer Research and Molecular Biology, having authored 6 papers that have together received 413 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Cancer Genomics and Diagnostics (2 papers) and Genomics and Rare Diseases (2 papers). The work is most often cited by research in Artificial Intelligence (295 citations), Molecular Biology (290 citations) and Health Informatics (5 citations). David Luis Wiegandt has collaborated with scholars based in Germany and United States. Frequent co-authors include Ulf Leser, Maryam Habibi, Leon Weber, Mariana Neves, Sophie Vieweg, Ulrich Keilholz, Daniel Koch, Damian Rieke, Mario Lamping and Fu Li. Their work appears in journals such as Nature Communications, Bioinformatics and BMC Bioinformatics.

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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