Philipp Daumke

29 papers receiving 674 citations

Hit Papers

Proceedings of the AMIA Symposium 2005 · 501 citations
5012005202620122019100200300400500

Peers

Philipp Daumke
Comparison fields: 5 of 113
  • Health Information Management 126
  • Health Informatics 25
  • Artificial Intelligence 377
  • Molecular Biology 331
  • Management Science and Operations Research 45
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Countries citing papers authored by Philipp Daumke

Since Specialization
Citations

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

Fields of papers citing papers by Philipp Daumke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Philipp Daumke, 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 Philipp Daumke Line = papers co-authored together Philipp Daumke links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20204
2
Aligning an Administrative Procedure Coding System with SNOMED CT.
20191
3 201916
4 20196
5 20199
6 20192
7
SEMCARE: Multilingual Semantic Search in Semi-Structured Clinical Data.
20163
8 201519
9
DebugIT: Ontology-mediated Layered Data Integration for Real-time Antibiotics Resistance Surveillance.
20143
10
German-Language Content in Biomedical Vocabularies.
20135
11 201222
12 20105
13 200817
14
Evaluation of a document search engine in a clinical department system.
200814
15 20076
16
Biomedical data mining in clinical routine: expanding the impact of hospital information systems.
20076
17
Semantic Atomicity and Multilinguality in the Medical Domain: Design Considerations for the MorphoSaurus Subword Lexicon.
20061
18
How to distinguish parthood from location in bioontologies.
20055
19
Proceedings of the AMIA Symposium
Hit paper breakdown →
2005501
20
Cross-language MeSH indexing using morpho-semantic normalization.
200312

About Philipp Daumke

Philipp Daumke is a scholar working on Anatomy, Health Information Management, Artificial Intelligence, Molecular Biology and Biophysics, having authored 29 papers that have together received 696 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (26 papers), Semantic Web and Ontologies (10 papers), Natural Language Processing Techniques (7 papers), Electronic Health Records Systems (4 papers), Topic Modeling (4 papers), Clinical practice guidelines implementation (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Information Management (126 citations), Health Informatics (25 citations), Artificial Intelligence (377 citations), Molecular Biology (331 citations) and Management Science and Operations Research (45 citations). Philipp Daumke has collaborated with scholars based in Germany, Austria and France. Frequent co-authors include Stefan Schulz, Udo Hahn, Barry Smith, Marcel L. Müller, Elmar Kotter, P. Fischer, Mathias Langer, Stefan Schulz, Percy Nohama and Rüdiger Klar. Their work appears in journals such as Der Ophthalmologe, Methods of Information in Medicine, Language Resources and Evaluation, European Radiology and RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren.

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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