Semantic Application for Healthcare

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Semantic application: how to integrate information

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Semantic Application for Healthcare

  1. 1. A semantic application for Healthcare Peter Scholten
  2. 2. 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.
  3. 3. Goal of semantic application • Social medium (twitter, hyves, facebook etc Communication • Discussion platform (Linkedin..) Business oriented • Information medium Questions like….
  4. 4. Semantic web for Healthcare What where to find
  5. 5. Benefits of the semantic web • Finding resources more quickly and easily • Storing corporate knowledge • To generate new knowledge • Improve the Clinic’s ability to use patient data for generating new knowledge to improve future patient care through outcomes-based and longitudinal clinical research. • Cross sectional data analysis
  6. 6. 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
  7. 7. Need for new semantic “functions” for information and knowledge processing
  8. 8. Example  Internet is collection documents with data mostly represented in tabular form with different formats and dimension.  How to integrate information
  9. 9. Health Care Civilians 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 Living place Age
  10. 10. Geographic distribution for care need
  11. 11. Geographic distribution for care need older then 65 years
  12. 12. Relation cardiologist and care takers older then 65 years
  13. 13. Relation family doctor and care takers region Brabant
  14. 14. • 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
  15. 15. • 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
  16. 16. Selected search internet: Demency
  17. 17. • 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
  18. 18. Inferencing Semantic web !
  19. 19. Example inferencing x zy
  20. 20. 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)
  21. 21. joints drugs
  22. 22. Health care informationmodel
  23. 23. Health care ontology Metadata (individuals) Metadata (individuals) Metadata (individuals) Metadata (individuals) Metadata (individuals)
  24. 24. Define Classes and the Class Hierarchy
  25. 25. 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.
  26. 26. Protégé: an ontology editor • RDF • RDFS • OWL • SPARQL
  27. 27. A typical relational database table for books
  28. 28. The rows represent the things you are storing information about
  29. 29. The columns represent the properties or attributes of those things
  30. 30. the book has a title with value "Javascript"
  31. 31. the book has a title with value "Javascript" subject has a property with object "value" (s,p,o) This is the essence of RDF: the (s,p,o) triple Any expression in RDF is a collection of triples
  32. 32. Relations Between Entities
  33. 33. RDF names things with URLs Create different URLs to name different things
  34. 34. Any RDF can be merged with any other RDF
  35. 35. 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>
  36. 36. 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.)
  37. 37. 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)
  38. 38. (X type C), (C subClassOf D) (X type D) Doctor Surgeon Anaesthesist rdfs: subClassOfrdfs: subClassOf Rdf:type If ?p rdf:type ?Surgeon If ?Surgeon rdfs: subClassOf ? Doctor Then ?p rdf:type ?Doctor
  39. 39. (X R Y), (R subPropertyOf Q) (X Q Y) worksFor freeLancesTo isEmployedBy rdfs: subPropertyOfrdfs: subPropertyOf ?p If ?p freeLancesTo ?Hospital If freeLancesTo rdfs: subPropertyOf worksFor Then ?p worksFor ?Hospital
  40. 40. domain range 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 ?Hospital hasSpecialism ?Physician ?Physician hasCompetences ?Competences
  41. 41. Terminology transfer Physician Specialism equivalent ? Physician rdfs: subClassOf ? Specialism
  42. 42. SPARQL
  43. 43. SPARQL (Query Language for RDF) SELECT ?hospital ?Physician WHERE { ?hospital rdf:value ?distance. ?physician category ?cardiologist. FILTER (?distance<=40). }
  44. 44. Searching internet Input: symptoms Output: Url’s for description symptoms
  45. 45. Searching internet Input: symptoms Output: Url’s for description symptoms
  46. 46. Searching internet Input: diseases or medicine Output: Url’s for description medicine and diseases
  47. 47. Searching internet Input: diseases or medicine Output: Url’s for description medicine and diseases
  48. 48. Searching internet Input: professional or institute Output: address
  49. 49. Searching internet Input: professional or institute Output: address
  50. 50. Searching internet Input: assistive device disabled persons Output: description and Url’s of assistive devices
  51. 51. Searching internet Input: assistive device disabled persons Output: description and Url’s of assistive devices What Where to find description detailed
  52. 52. 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

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