Philipp Daumke

29 papers receiving 680 citations

Philipp Daumke's Hit Papers

Proceedings of the AMIA Symposium 2005 · 506 citations
5060+7+14Years since publication100200300400500

Peers

Philipp Daumke
Comparison fields: 5 of 105
  • Health Information Management 93
  • Health Informatics 20
  • Artificial Intelligence 272
  • Molecular Biology 253
  • Management Science and Operations Research 38
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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-authors

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

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Proceedings of the AMIA Symposium
Hit paper breakdown →
2005506
2 201222
3 201519
4 200817
5 201916
6
Evaluation of a document search engine in a clinical department system.
200814
7
Cross-language MeSH indexing using morpho-semantic normalization.
200312
8
Interlingual indexing across different languages
200411
9 20199
10 20197
11 20227
12 20076
13
Biomedical data mining in clinical routine: expanding the impact of hospital information systems.
20076
14
German-Language Content in Biomedical Vocabularies.
20135
15 20135
16 20105
17
How to distinguish parthood from location in bioontologies.
20055
18
Large-scale evaluation of a medical cross-language information retrieval system.
20075
19 20204
20 20214

About Philipp Daumke

Philipp Daumke is a scholar working on Molecular Biology, Artificial Intelligence, Health Information Management, Radiology, Nuclear Medicine and Imaging and Management Science and Operations Research, having authored 29 papers that have together received 702 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (19 papers), Semantic Web and Ontologies (9 papers), Natural Language Processing Techniques (5 papers), Electronic Health Records Systems (4 papers), Topic Modeling (3 papers), Medical and Biological Sciences (2 papers), Data Quality and Management (2 papers) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Health Information Management (93 citations), Health Informatics (20 citations), Artificial Intelligence (272 citations), Molecular Biology (253 citations) and Management Science and Operations Research (38 citations). Philipp Daumke has collaborated with scholars based in Germany, Austria and United States. Frequent co-authors include Stefan Schulz, Udo Hahn, Barry Smith, Marcel L. Müller, P. Fischer, Elmar Kotter, Mathias Langer, Rüdiger Klar, Percy Nohama and Catalina Martínez-Costa. Their work appears in journals such as Methods of Information in Medicine, Der Ophthalmologe, RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, European Radiology and Language Resources and Evaluation.

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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