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Semantic Application for Healthcare

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Semantic application: how to integrate information

Semantic application: how to integrate information

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    Semantic Application for Healthcare Semantic Application for Healthcare Presentation Transcript

    • A semanticapplication
      for HealthcarePeter Scholten
    • How to build a semantic application
      What is the goal of a semantic application.
      Not only focused on known requirements, but also anticipate on unknown…’future’ settings.
    • Goal of semantic application
      Social medium (twitter, hyves, facebooketc
      Communication
      Discussion platform (Linkedin..)
      Business oriented
      Information medium
      Questions like….
    • Semantic web for Healthcare
      What
      where to find
    • Benefits of the semantic web
      • Finding resources more quicklyandeasily
      • Storing corporate knowledge
      • Togenerate new knowledge
      • Improvethe Clinic’sabilitytousepatient data for
      generatingnew knowledgetoimprovefuturepatient care
      throughoutcomes-basedandlongitudinalclinical research.
      • Cross sectional data analysis
    • Problems on internet
      Format
      Language
      Homograph: group of words that share the same spelling but have different meanings
      Homonym: group of words that share the same spelling or pronunciation (or both) but have different meanings
      Synonym: different words with identical or at least similar meanings
      Polysemy: the capacity for a word to have multiple meanings
    • Need for new semantic “functions” for
      information and knowledge processing
    • Example
      • Internet is collection documents with data mostly represented in tabular form with different formats and dimension.
      • How to integrate information
    • Civilians
      Health Care
      Living place
      Age
      How to define
      • Relation care takers and care need
      • Relation care takers and care need depending living place
      • Relation care takers and care need of older people depending living place
      Age
    • Geographic distribution for care need
    • Geographic distribution for care need older then 65 years
    • Relation cardiologist and care takers older then 65 years
    • Relation family doctor and care takers region Brabant
    • Find models on the web
      RFD/XML files
      Direct access to selected documents
      Special Google search
      Built a model from scratch
      SQL versus relational database
      Use of inferencing
    • Find models on the web
      RFD/XML files
      Direct access to selected documents
      Special Google search
      Built a model from scratch
      SQL versus relational database
      Use of inferencing
    • Selected search internet: Demency
    • Find models on the web
      RFD/XML files
      Direct access to selected documents
      Special Google search
      Built a model from scratch
      SQL versus relational database
      Use of inferencing
    • Inferencing
      Semantic web !
    • Example inferencing
      z
      y
      x
    • An Ontology
      Defines
      a common vocabulary
      a shared understanding
      re-use of domain knowledge.
      Is an explicit description of a domain:
      Concepts (classes, subclasses and superclasses)
      properties and attributes of concepts
      constraints on properties and attributes
      Individuals (often, but not always)
    • joints
      drugs
    • Health care informationmodel
    • Metadata (individuals)
      Metadata (individuals)
      Metadata (individuals)
      Metadata (individuals)
      Metadata (individuals)
      Health care ontology
    • Define Classes and the Class Hierarchy
    • Description of domain by RDF
      RDF: Resource Description Framework
      is a data model for representing metadata (information about Resources = URI)
      in the World Wide Web.
    • Protégé: an ontology editor
      RDF
      RDFS
      OWL
      SPARQL
    • A typicalrelational database tableforbooks
    • The rows represent the things you are storing
      information about
    • The columns represent the properties or
      attributes of thosethings
    • the book has a title with value "Javascript"
    • the book has a titlewithvalue"Javascript"
      subject has a propertywithobject "value" (s,p,o)
      This is the essence of RDF: the (s,p,o) triple
      Any expression in RDF is a collection of triples
    • Relations Between Entities
    • RDF names things with URLs
      Create different URLs to name different things
    • Any RDF can be merged with any other RDF
    • Storage of RDF’s in an XML document with the tag rdf:RDF
      The content of an XML document is a number of descriptions, which use rdf:Description tags.
      <rdf:RDF
      xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
      xmlns:mydomain="http://www.mydomain.org/my-rdf-ns">
      <rdf:Description
      rdf:about="http://www.cit.gu.edu.au/~db">
      <mydomain:site-owner
      rdf:resource=“#David Billington“/>
      </rdf:Description>
      </rdf:RDF>
    • rdfs
      RDFS is a vocabulary description language, using
      Classes and Properties
      Class Hierarchies and Inheritance
      Property Hierarchies
      OWL/OWL2:
      A richer ontology language, disjointness, cardinality, characteristics of properties
      (SymmetricProperty, TransitiveProperty, and inverseOf, FunctionalProperty,
      InverseFunctional-Property, sameAs.)
    • Some RDFS inference rules
      • (X R Y), (R subPropertyOf Q) (X Q Y)
      • (X R Y), (R domain C) (X type C)
      • (X type C), (C subClassOf D) (X type D)
    • (X type C), (C subClassOf D) (X type D)
      Doctor
      rdfs: subClassOf
      rdfs: subClassOf
      Anaesthesist
      Surgeon
      Rdf:type
      If ?p rdf:type ?Surgeon
      If ?Surgeon rdfs: subClassOf ? Doctor
      Then ?p rdf:type ?Doctor
    • (X R Y), (R subPropertyOf Q) (X Q Y)
      worksFor
      rdfs: subPropertyOf
      rdfs: subPropertyOf
      isEmployedBy
      freeLancesTo
      ?p
      If ?p freeLancesTo ?Hospital
      If freeLancesTordfs: subPropertyOfworksFor
      Then ?p worksFor ?Hospital
    • ?Hospital hasSpecialism ?Physician
      ?Physician hasCompetences ?Competences
      range
      domain
      If P(PROPERTY)rdfs: domain D and x P Y then x rdf: type D
      If P(PROPERTY) rdfs: range R and x P Y then y rdf: type R
    • Terminology transfer
      Specialism
      Physician
      equivalent
      ? Physician rdfs: subClassOf ? Specialism
    • SPARQL
    • SPARQL (Query Language for RDF)
      SELECT ?hospital ?Physician
      WHERE { ?hospital rdf:value ?distance.
      ?physician category ?cardiologist.
      FILTER (?distance<=40). }
    • Searching internet
      Input: symptoms
      Output: Url’s for description symptoms
    • Searching internet
      Input: symptoms
      Output: Url’s for description symptoms
    • Searching internet
      Input: diseases or medicine
      Output: Url’s for description medicine and diseases
    • Searching internet
      Input: diseases or medicine
      Output: Url’s for description medicine and diseases
    • Searching internet
      Input: professional or institute
      Output: address
    • Searching internet
      Input: professional or institute
      Output: address
    • Searching internet
      Input: assistive device disabled persons
      Output: description and Url’s of assistive devices
    • Searching internet
      Input: assistive device disabled persons
      Output: description and Url’s of assistive devices
      detailed
      What
      Where to find
      description
    • Searching internet
      Input:
      assistive need for older or disabled persons
      • Aids for low-vision or blind persons
      • Aids for motor disabilities
      • Persons hard of hearing
      • Demency
      • COPD
      • Chronic diseases
      • Home care
      • Emergency service
      Output:
      description and Url’s of assistive advice