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Biomedical subjects

Udo Hahn

Publications and source records attributed to Udo Hahn.

17 recordsLinked to original sources
PubMed2006

Automatic lexeme acquisition for a multilingual medical subword thesaurus.

PURPOSE: We present a method for the automated acquisition of a multilingual medical lexicon (for Spanish, French and Swedish) to be used within the framework of a medical cross-language text retrieval system. METHODS: For the lexical acquisition process, we incorporate seed lexicons and lists of trusted term translations derived from the UMLS Metathesaurus. The seed lexicons for Spanish, French and Swedish are automatically generated from (previously manually constructed) Portuguese, German and English sources by simple string transformations. Lexical and semantic hypotheses are then validated by processing pairs of term translations. In a last step, we use the cleaned list of "approved" translations in order to augment, step by step, the target dictionaries by processing the parallel corpora in terms of co-occurrence patterns of hypothesized translation equivalents which cannot be derived by simple character substitutions. RESULTS: An existing multilingual lexicon for the medical domain with about 60,000 entries for English, German, and Portuguese was automatically augmented by more then 17,000 new lexemes for Spanish, French, and Swedish. CONCLUSIONS: Our approach constitutes a promising method for the automated creation of new lexicon entries and their linkage to semantic identifiers.

Electronic Data Processing↗
PubMed2006

A language classifier that automatically divides medical documents for experts and health care consumers.

We propose a pipelined system for the automatic classification of medical documents according to their language (English, Spanish and German) and their target user group (medical experts vs. health care consumers). We use a simple n-gram based categorization model and present experimental results for both classification tasks. We also demonstrate how this methodology can be integrated into a health care document retrieval system.

Germany↗
PubMed2006

Cross-lingual alignment of biomedical acronyms and their expansions.

We propose a method that aligns biomedical acronyms and their definitions across different languages. The approach is based upon a freely available tool for the extraction of abbreviations together with their expansions, and the subsequent normalization of language-specific variants, synonyms, and translations of the extracted acronym definitions. In this step, acronym expansions are mapped onto a language-independent concept-layer on which intra- as well as interlingual comparisons are drawn.

Germany↗
PubMed2005

Towards new information resources for public health--from WordNet to MedicalWordNet.

In the last two decades, WordNet has evolved as the most comprehensive computational lexicon of general English. In this article, we discuss its potential for supporting the creation of an entirely new kind of information resource for public health, viz. MedicalWordNet. This resource is not to be conceived merely as a lexical extension of the original WordNet to medical terminology; indeed, there is already a considerable degree of overlap between WordNet and the vocabulary of medicine. Instead, we propose a new type of repository, consisting of three large collections of (1) medically relevant word forms, structured along the lines of the existing Princeton WordNet; (2) medically validated propositions, referred to here as medical facts, which will constitute what we shall call MedicalFactNet; and (3) propositions reflecting laypersons' medical beliefs, which will constitute what we shall call the MedicalBeliefNet. We introduce a methodology for setting up the MedicalWordNet. We then turn to the discussion of research challenges that have to be met to build this new type of information resource. We build a database of sentences relevant to the medical domain. The sentences are generated from WordNet via its relations as well as from medical statements broken down into elementary propositions. Two subcorpora of sentences are distinguished, MedicalBeliefNet and MedicalFactNet. The former is rated for assent by laypersons; the latter for correctness by medical experts. The sentence corpora will be valuable for a variety of applications in information retrieval as well as in research in linguistics and psychology with respect to the study of expert and non-expert beliefs and their linguistic expressions. Our work has to meet several considerable challenges. These include accounting for the distinction between medical experts and laypersons, the social issues of expert-layperson communication in different media, the linguistic aspects of encoding medical knowledge, and the reliability, volume, and emergence of medical knowledge. The work described here has been tested in a small pilot experiment and awaits large-scale implementation.

Computational Biology↗
PubMed2005

Part-whole representation and reasoning in formal biomedical ontologies.

OBJECTIVE: Biomedical ontologies are typically structured in a biaxial way, reflecting both a taxonomic (is-a) and a partonomic (part-of) hierarchy. Commonly used biomedical terminologies, which incorporate such distinctions excel in terms of broad coverage but lack a rigid formal foundation. The latter, however, is a prerequisite for automated reasoning. For the biomedical domain, it is not only crucial to cope with ontological dependencies between wholes and their parts but also with specific reasoning patterns which underlie the propagation of roles across partonomic hierarchies. METHODS: We scale down part-whole reasoning to subsumption-based taxonomic reasoning within the formal framework of a parsimonious variant of description logics (viz. ALC). RESULTS: We provide a formal basis for ontological engineering in the domain of biomedicine, as far as part-whole relationships are concerned, by addressing typical reasoning patterns encountered in this domain.

Artificial Intelligence↗
PubMed2005

Semantic Clarification of the Representation of Procedures and Diseases in SNOMED((R))CT.

SNOMED((R)) CT is emerging as a reference terminology for the entire health care process. It claims to be founded on logic-based modeling principles. In this work we analyze a special encoding scheme for SNOMED disease and procedure entities, the so-called relationship groups which had been devised in order to avoid ambiguities in entity definitions. We show that these artifacts may represent hidden mereological relations. We also report discrepancies encountered between the defined semantics of many SNOMED((R)) CT entity terms and their intuitive meaning, and inconsistencies detected between the definition of some complex composed entities and the definition of their top-level parents. As a result we formulate recommendations for improvements of SNOMED((R)) CT.

Humans↗
PubMed2005

Automatic lexicon acquisition for a medical cross-language information retrieval system.

We present a method for the automated acquisition of a multilingual medical lexicon (for Spanish and Swedish) to be used within the framework of a medical cross-language text retrieval system. We incorporate seed lexicons and parallel corpora derived from the UMLS Metathesaurus. The seed lexicons for Spanish and Swedish are automatically generated from (previously manually constructed) Portuguese, German and English sources. Lexical and semantic hypotheses are then validated making iterative use of co-occurrence patterns of hypothesized translation synonyms in the parallel corpora.

Humans↗
PubMed2005

How to distinguish parthood from location in bioontologies.

The pivotal role of the relation part-of in the description of living organisms is widely acknowledged. Organisms are open systems, which means that in contradistinction to mechanical artifacts they are characterized by a continuous flow and exchange of matter. A closer analysis of the spatial relations in biological organism reveals that the decision as to whether a given particular is part-of a second particular or whether it is only contained-in the second particular may often be controversial. We here propose a rule-based approach which allows us to decide on the basis of well-defined criteria which of the two relations holds between two anatomical objects, given that one spatially includes the other. We discuss the advantages and limitations of this approach, using concrete examples from human anatomy.

Algorithms↗
PubMed2005

Effective grading of termhood in biomedical literature.

The ever-increasing amount of textual information in biomedicine calls for effective procedures for automatic terminology extraction which assist biomedical researchers and professionals in gathering and organizing terminological knowledge encoded in text documents. In this study, we propose a new, linguistically grounded measure for automatically identifying multi-word terms from the biomedical literature. Our approach is based on the limited paradigmatic modifiability of terms and is tested on bigram, trigram and quadgram noun phrases extracted from a 104-million-word text corpus comprised of Medline abstracts. Using the UMLS Metathesaurus as a gold standard, we show that our algorithm substantially outperforms the standard term identification measures and, therefore, qualifies as a high-performing building block for any biomedical terminology mining system.

Algorithms↗
PubMed2004

Really, is medical sublanguage that different? Experimental counter-evidence from tagging medical and newspaper corpora.

We compare the performance of two part-of-speech taggers trained on a German newspaper corpus for mixed types of medical documents. TnT, a tagger based on a statistical language model, outperforms Brill's rule-based tagger, and supplied with additional lexicon resources matches state-of-the-art performance figures (close to 97% accuracy) on the medical corpus. We explain this unexpected result by focusing on the statistically significant part-of-speech type overlap between the newspaper training set and the medical test set. At least at that level, sublanguage differences seem to vanish. Thus, statistical off-the-shelf part-of-speech taggers can immediately be reused for medical language processing

Natural Language Processing↗
PubMed2004

A description logics approach to CGPS.

We develop a formal framework by which clinical guidelines and protocols (CGPs) can be partially represented as a set of terminological concept definitions using standard description logics. There are two benefits in pursuing such an approach. First, it provides a foundation for logic-based CGP fusion and collision detection. Second, it allows for the checking of clinical treatment episodes from the EPR against CGPs.

Artificial Intelligence↗
PubMed2003

Cross-language MeSH indexing using morpho-semantic normalization.

We consider three alternative procedures for the automatic indexing of medical documents using MeSH thesaurus identifiers as target units (document descriptors). Rather than considering complete words as the starting point of the indexing procedure, we here propose morphologically plausible subwords as basic units from which MeSH terms are derived. We describe the morphological segmentation and normalization procedures, as well as the mappings from subwords to MeSH terms, and discuss results from an evaluation carried out on a German-language corpus.

Abstracting and Indexing↗
PubMed2002

MEDSYNDIKATE--a natural language system for the extraction of medical information from findings reports.

MEDSYNDIKATE is a natural language processor, which automatically acquires medical information from findings reports. In the course of text analysis their contents is transferred to conceptual representation structures, which constitute a corresponding text knowledge base. MEDSYNDIKATE is particularly adapted to deal properly with text structures, such as various forms of anaphoric reference relations spanning several sentences. The strong demands MEDSYNDIKATE poses on the availability of expressive knowledge sources are accounted for by two alternative approaches to acquire medical domain knowledge (semi)automatically. We also present data for the information extraction performance of MEDSYNDIKATE in terms of the semantic interpretation of three major syntactic patterns in medical documents.

Confidence Intervals↗
PubMed2002

Creating knowledge repositories from biomedical reports: the MEDSYNDIKATE text mining system.

MEDSYNDIKATE is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The system architecture integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MEDSYNDIKATE poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering. We also present data for the knowledge extraction performance of MEDSYNDIKATE for three major syntactic patterns in medical documents.

Confidence Intervals↗
PubMed2002

A knowledge representation view on biomedical structure and function.

In biomedical ontologies, structural and functional considerations are of outstanding importance, and concepts which belong to these two categories are highly interdependent. At the representational level both axes must be clearly kept separate in order to support disciplined ontology engineering. Furthermore, the biaxial organization of physical structure (both by a taxonomic and partonomic order) entails intricate patterns of inference. We here propose a layered encoding of taxonomic, partonomic and functional aspects of biomedical concepts using description logics.

Artificial Intelligence↗
PubMed2002

Text retrieval based on medical subwords.

In biomedical documents, there is ample evidence for complex morphological structures in specialized terms. While inflection is relatively easy to deal with, productive morphological processes such as derivation and single-word composition constitute a major challenge. Considering the problem from an information retrieval perspective, we split morphologically complex words into biomedically significant, morpheme-like subwords and match subwords the query terms and document terms are composed of. This way, morphologically motivated word form alterations can be eliminated from the retrieval procedure. Based on a series of retrieval experiments, we have gathered evidence that subword-based indexing and retrieval for the German biomedical sublanguage, at least--outperforms conventional string matching approaches.

Germany↗