Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Patient-Generated EHR Input System Trials: An Analysis of Perceived Benefits Across a Range of Disease Groups Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

2. Utilizing Semantic Web Technologies in Healthcare

verfasst von : Vassileios D. Kolias, John Stoitsis, Spyretta Golemati, Konstantina S. Nikita

Erschienen in: Concepts and Trends in Healthcare Information Systems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The technological breakthrough in biomedical engineering and health informatics has produced several Health Information Systems (HIS) and medical devices that are used on a daily basis in hospitals producing a vast amount of data. The data that are produced come from different sources and are not stored in a unified storage repository or database even in a single hospital. As a result of that the interoperability of HIS is limited, the retrieval of information is difficult and there is hidden knowledge that remains unexploited in vast and diverse pools of medical data. In order to overcome the above, scientific community suggests the use of the semantic web technologies. The semantic web technologies provide the tools that allow to process data in a more effective and accurate way, create the framework for interoperability between HIS and also integrate data from various sources with their semantic meaning

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Patient-Generated EHR Input System Trials: An Analysis of Perceived Benefits Across a Range of Disease Groups
Nächstes Kapitel Exploiting Ontology Based Search and EHR Interoperability to Facilitate Clinical Trial Design
Fußnoten
Literatur
Akgül CB, Rubin DL, Napel S, Beaulieu CF, Greenspan H, Acar B (2011) Content-based image retrieval in radiology: current status and future directions. J Digit Imaging 24:208–222CrossRef
Belleau F, Nolin M-A, Tourigny N, Rigault P, Morissette J (2008) Bio2RDF: towards a mashup to build bioinformatics knowledge systems. J Biomed Inform 41:706–716CrossRef
Berners-Lee T, Hendler J, Lassila O (2001) The semantic web. Sci Am 284:28–37
Bodenreider O (2004) The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Res 32:D267–D270
Burgun A (2006) Desiderata for domain reference ontologies in biomedicine. J Biomed Inf 39:307–313
Chen R, Georgii-Hemming P, Åhlfeldt H (2009) Representing a chemotherapy guideline using openEHR and rules. In: MIE. pp 653–657
Ferreira JD, Paolotti D, Couto FM, Silva MJ (2013) On the usefulness of ontologies in epidemiology research and practice. J Epidemiol Community Health 67:385–388
Gruber TR (1993) A translation approach to portable ontology specifications. Knowl Acquis 5:199–220
Hare JS, Lewis PH, Enser PGB, Sandom CJ (2006) Mind the gap: another look at the problem of the semantic gap in image retrieval. 607309-607309-12
Kalra D, Beale T, Heard S (2005) The openEHR foundation. Studies Health Technol Inf 115:153–173
Kyriazos G, Gerostathopoulos I, Kolias V, STOITSIS J, Nikita KA (2011) semantically-aided approach for online annotation and retrieval of medical images. Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE. IEEE 2372–2375
Langlotz CP (2006) RadLex: A new method for indexing online educational materials1. Radiographics 26:1595–1597CrossRef
Lezcano L, Sicilia M-A, Serrano-Balazote P (2008) Combining OpenEHR archetype definitions with SWRL rules—a translation approach. Emerging technologies and information systems for the knowledge society. Springer, Berlin, pp 79–87
Lezcano L, Sicilia M-A, Rodríguez-Solano C (2011) Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules. J Biomed Inf 44:343–353
Mejino JL Jr, Rubin DL, Brinkley JF (2008) FMA-RadLex: An application ontology of radiological anatomy derived from the foundational model of anatomy reference ontology. AMIA Annual Symposium Proceedings, 2008. American Medical Informatics Association, p 465
Möller M, Sintek M (2007) A generic framework for semantic medical image retrieval. KAMC 253
Möller M, Regel S, Sintek M (2009) Radsem: Semantic annotation and retrieval for medical images. In: The semantic web: research and applications. Springer, Berlin, pp 21–35
Möller M, Sintek M, Biedert R, Ernst P, Dengel A, Sonntag D (2010) Representing the International Classification of Diseases Version 10 in OWL. KEOD. 50–59
Pérez-Rey D, Maojo V, García-Remesal M, Alonso-Calvo R, Billhardt H, Martín-Sánchez F, Sousa A (2006) ONTOFUSION: Ontology-based integration of genomic and clinical databases. Comput Biol Med 36:712–730CrossRef
Rosse C, Mejino JL Jr (2003) A reference ontology for biomedical informatics: the foundational model of anatomy. J Biomed Inf 36:478–500
Rubin DL, Grossman D, Neal M, Cook DL, Bassingthwaighte JB, Musen MA (2006a) Ontology-based representation of simulation models of physiology. AMIA Annual Symposium Proceedings. American Medical Informatics Association, p 664
Rubin DL, Lewis SE, Mungall CJ, Misra S, Westerfield M, Ashburner M, Sim I, Chute CG, Storey M-A, Smith B (2006b) National center for biomedical ontology: advancing biomedicine through structured organization of scientific knowledge. Omics: J Integr Bio 10:185–198
Rubin DL, Mongkolwat P, Kleper V, Supekar K, Channin DS (2009) Annotation and image markup: accessing and interoperating with the semantic content in medical imaging. Intelligent systems. IEEE 24:57–65
Ryan A (2006) Towards semantic interoperability in healthcare: ontology mapping from SNOMED-CT to HL7 version 3. Proceedings of the second Australasian workshop on Advances in ontologies-Volume 72. Australian Computer Society, Inc., 69–74
Ryan A, Eklund P, Esler B (2007) Toward the interoperability of HL7 v3 and SNOMED CT: a case study modeling mobile clinical treatment
Sari AK, Rahayu W, Bhatt M (2013) An approach for sub-ontology evolution in a distributed health care enterprise. Info Syst 38:727–744CrossRef
Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone S-A, Scheuermann RH, Shah N, Whetzel PL, Lewis S (2007) The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotech 25:1251–1255CrossRef
Stearns MQ, Price C, Spackman KA, Wang AY, SNOMED clinical terms (2001) Overview of the development process and project status. Proceedings of the AMIA Symposium. American Medical Informatics Association, p 662
Tudorache T, Falconer S, Noy NF, Nyulas C, Üstün TB, Storey M-A, Musen MA (2010) Ontology development for the masses: creating ICD-11 in WebProtégé. In: Ciniano P, Pinto HS (ed) Knowledge engineering and management by the masses. Springer, Berlin, pp 74–89
Tudorache T, Nyulas CI, Noy NF, Musen MA (2013) Using Semantic Web in ICD-11: three years down the road. In: The semantic web –ISWC 2013. Springer, Berlin, pp 195–211
Viklund H, Karlsson H (2009) Clinical decision support rules in an archetype-based health record system: combining Archetype Query Language (AQL) and Semantic Web Rule Language (SWRL). Linköping
Metadaten
Titel
Utilizing Semantic Web Technologies in Healthcare
verfasst von
Vassileios D. Kolias
John Stoitsis
Spyretta Golemati
Konstantina S. Nikita
Copyright-Jahr
2014
Buch
Concepts and Trends in Healthcare Information Systems

Print ISBN: 978-3-319-06843-5

Electronic ISBN: 978-3-319-06844-2

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-06844-2_2