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Researcher · TU Wien · Austria

Silvia Miksch

Silvia Miksch publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, on topics such as Data Visualization and Analytics, Semantic Web and Ontologies and Biomedical Text Mining and Ontologies.

ORCID 0000-0003-4427-5703 OpenAlex
World rank
#333,314
of 7,710,434 ranked researchers
Rank in Austria
#2,324
of 43,330
Works
349
Citations
8.9k
Citations per work
25.5
h-index
47
i10-index 151Top 1.4% in Computer Vision and Pattern Recognition
Silvia Miksch

What does Silvia Miksch research?

Silvia Miksch's work is mostly in Computer Science (50%), Biochemistry, Genetics and Molecular Biology (6%), Health Professions (3%).

Physical Sciences: 176 works · 50.5% of their workComputer Science: 176 works · 50.5% of their workComputer Vision and Pattern Recognition: 96 works · 27.4% of their workArtificial Intelligence: 56 works · 16.1% of their workSignal Processing: 24 works · 7.0% of their workEverything else: 128 works · 36.8% of their workHealth Sciences: 23 works · 6.6% of their workHealth Professions: 12 works · 3.3% of their workHealth Information Management: 12 works · 3.3% of their workMedicine: 12 works · 3.3% of their workPublic Health, Environmental and Occupational Health: 12 works · 3.3% of their workLife Sciences: 21 works · 6.1% of their workBiochemistry, Genetics and Molecular Biology: 21 works · 6.1% of their workMolecular Biology: 21 works · 6.1% of their workTHEIR WORKSilvia Miksch349works
Life Sciences6%Physical Sciences50%Health Sciences7%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science17650.5%
  2. Everything else12836.8%
    1. Health Professions123.3%
    2. Medicine123.3%
    1. Biochemistry, Genetics and Molecular Biology216.1%
  1. 1Computer Vision and Pattern Recognition27% of their works
  2. 2Artificial Intelligence16% of their works
  3. 3Signal Processing7% of their works
  4. 4Molecular Biology6% of their works
  5. 5Public Health, Environmental and Occupational Health3% of their works
  6. 6Health Information Management3% of their works

Research topics

Which keywords describe Silvia Miksch's research?

The keywords of their largest research topics: Information Visualization, Visual Analytics, Data Integration, Semantic Web, Linked Data, Ontology, Biomedical Ontologies and Text Mining.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 18 words, with their numbers
  1. Information Visualization1861 topic
  2. Visual Analytics1861 topic
  3. Data Integration1222 topics
  4. Semantic Web1222 topics
  5. Linked Data681 topic
  6. Ontology681 topic
  7. Biomedical Ontologies541 topic
  8. Text Mining541 topic
  9. Content-Based Retrieval401 topic
  10. Video Summarization401 topic
  11. Clustering301 topic
  12. Time Series301 topic
  13. Clinical Decision Support Systems281 topic
  14. Clinical Guidelines281 topic
  15. Electronic Health Records281 topic
  16. Guideline Development281 topic
  17. GPS Trajectories271 topic
  18. Trajectory Data Mining271 topic

Where does Silvia Miksch work?

Silvia Miksch's main affiliation in the publication record is TU Wien, Austria.

How many publications and citations does Silvia Miksch have?

OpenAlex counts 349 works and 8,888 citations for Silvia Miksch, an h-index of 47, ranking #333,314 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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