# How knowledge drives understanding—matching medical ontologies with the needs of medical language processing

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/how-knowledge-drives-understanding-matching-medical-ontologies-with-the-needs-of/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Udo Hahn,Martin Romacker,Stefan Schulz |
| Citations | 60 |
| DOI | 10.1016/s0933-3657(98)00044-x |
| Fields | Biochemistry, Genetics and Molecular Biology,Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W1986727175 |
| PMID | 9930615 |
| Type | article |
| Year | 1999 |

## Paper authors

- [Stefan Schulz](https://scholariq.org/researchers/stefan-schulz/)

## Paper journal

- [Artificial Intelligence in Medicine](https://scholariq.org/journals/artificial-intelligence-in-medicine/)

## Paper primary topic

- [Biomedical Text Mining and Ontologies](https://scholariq.org/topics/biomedical-text-mining-and-ontologies/)

## Paper topics

- [Biomedical Text Mining and Ontologies](https://scholariq.org/topics/biomedical-text-mining-and-ontologies/)
- [Semantic Web and Ontologies](https://scholariq.org/topics/semantic-web-and-ontologies/)
- [Natural Language Processing Techniques](https://scholariq.org/topics/natural-language-processing-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.