Extending the TOP Framework with an Ontology-Based Text Search Component.

Journal: Studies in health technology and informatics

PMID: 39234721

Abstract

INTRODUCTION: Constructing search queries that deal with complex concepts is a challenging task without proficiency in the underlying query language - which holds true for either structured or unstructured data. Medical data might encompass both types, with valuable information present in one type but not the other.

Authors

Franz Matthies

Jena University Language & Information Engineering (JULIE) Lab Friedrich-Schiller-Universität Jena, Jena, Germany.
Christoph Beger

University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology.
Ralph Schäfermeier

Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University.
Konrad Höffner

IMISE, University of Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany.
Alexandr Uciteli

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany.

Keywords

Data Mining Electronic Health Records Humans Information Storage and Retrieval Natural Language Processing

External Resources

View on PubMed Access via DOI PubMed (39234721)

Extending the TOP Framework with an Ontology-Based Text Search Component.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals