Stammdaten

Concept-Based and Multimodal Methods for Medical Case Retrieval
Untertitel:
Kurzfassung:

Medical case retrieval (MCR) is defined as a multimedia retrieval problem, where the document collection consists of medical case descriptions that pertain to particular diseases, patients' histories, or other entities of biomedical knowledge. Case descriptions are multimedia documents containing textual and visual modalities (images). A query may consist of a textual description of patient's symptoms and related diagnostic images. This thesis proposes and evaluates methods that aim at improving MCR effectiveness over the baseline of fulltext retrieval. We hypothesize that this objective can be achieved by utilizing controlled vocabularies of biomedical concepts for query expansion and concept-based retrieval. The latter represents case descriptions and queries as vectors of biomedical concepts, which may be generated automatically from textual and/or visual modalities by concept mapping algorithms. We propose a multimodal retrieval framework for MCR by late fusion of text-based retrieval (including query expansion) and concept-based retrieval and show that retrieval effectiveness can be improved by 49% using linear fusion of practical component retrieval systems. The potential of further improvement is experimentally estimated as a 166% increase of effectiveness over fulltext retrieval using query-adaptive fusion of ideal component retrieval systems. Additional contributions of this thesis include the proposal and comparative evaluation of methods for concept mapping, query and document expansion, and automatic classification and separation of compound figures found in case descriptions.

Schlagworte:
Publikationstyp: Hochschulschrift (nicht publiziert) (Autorenschaft)
Art der Veröffentlichung Printversion
Erscheinungdatum: 05.2017
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Gesamtseitenanzahl: 200 S.

Identifikatoren

ISBN: -
ISSN: -
DOI: -
AC-Nummer: -
Homepage: https://www-itec.uni-klu.ac.at/bib/files/phd-thesis-taschwer.pdf
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020  Klagenfurt am Wörthersee
Österreich
  -3699
   martina.steinbacher@uni-klu.ac.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Verlag

Organisation Adresse
Alpen-Adria-Universität Klagenfurt (Eigenverlag)
Universitätsstraße 65-67
9020  Klagenfurt am Wörthersee
Österreich
  +43 463 2700-9200
  +43463 2700-9299
   uni@aau.at
http://www.aau.at
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Nein
Publikationsfokus
  • Science to Science (Qualitätsindikator: n.a.)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Distributed Multimedia Systems

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