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A semantic application
for Healthcare
Peter 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, facebook etc
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 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
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
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
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
x
zy
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
Health care ontology
Metadata
(individuals)
Metadata
(individuals)
Metadata
(individuals)
Metadata
(individuals)
Metadata
(individuals)
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 typical relational database table for books
The rows represent the things you are storing
information about
The columns represent the properties or
attributes of those things
the book has a title with value "Javascript"
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
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
Surgeon Anaesthesist
rdfs: subClassOfrdfs: subClassOf
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
freeLancesTo isEmployedBy
rdfs: subPropertyOfrdfs: subPropertyOf
?p
If ?p freeLancesTo ?Hospital
If freeLancesTo rdfs: subPropertyOf worksFor
Then ?p worksFor ?Hospital
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
Terminology transfer
Physician Specialism
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
What
Where to find
description
detailed
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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Semantic Application for Healthcare

  • 1. A semantic application for Healthcare Peter Scholten
  • 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. Goal of semantic application • Social medium (twitter, hyves, facebook etc Communication • Discussion platform (Linkedin..) Business oriented • Information medium Questions like….
  • 4. Semantic web for Healthcare What where to find
  • 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.
  • 7. 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
  • 8. Need for new semantic “functions” for information and knowledge processing
  • 9. Example  Internet is collection documents with data mostly represented in tabular form with different formats and dimension.  How to integrate information
  • 10. 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
  • 12. Geographic distribution for care need older then 65 years
  • 13. Relation cardiologist and care takers older then 65 years
  • 14. Relation family doctor and care takers region Brabant
  • 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. • 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. • 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
  • 21.
  • 22. 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)
  • 26. Define Classes and the Class Hierarchy
  • 27. 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.
  • 28. Protégé: an ontology editor • RDF • RDFS • OWL • SPARQL
  • 29.
  • 30. A typical relational database table for books
  • 31. The rows represent the things you are storing information about
  • 32. The columns represent the properties or attributes of those things
  • 33. the book has a title with value "Javascript"
  • 34. 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
  • 36. RDF names things with URLs Create different URLs to name different things
  • 37. Any RDF can be merged with any other RDF
  • 38. 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>
  • 39. 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.)
  • 40.
  • 41. 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)
  • 42. (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
  • 43. (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
  • 44. 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
  • 45. Terminology transfer Physician Specialism equivalent ? Physician rdfs: subClassOf ? Specialism
  • 46.
  • 48. SPARQL (Query Language for RDF) SELECT ?hospital ?Physician WHERE { ?hospital rdf:value ?distance. ?physician category ?cardiologist. FILTER (?distance<=40). }
  • 49.
  • 50. Searching internet Input: symptoms Output: Url’s for description symptoms
  • 51. Searching internet Input: symptoms Output: Url’s for description symptoms
  • 52. Searching internet Input: diseases or medicine Output: Url’s for description medicine and diseases
  • 53. Searching internet Input: diseases or medicine Output: Url’s for description medicine and diseases
  • 54. Searching internet Input: professional or institute Output: address
  • 55. Searching internet Input: professional or institute Output: address
  • 56. Searching internet Input: assistive device disabled persons Output: description and Url’s of assistive devices
  • 57. Searching internet Input: assistive device disabled persons Output: description and Url’s of assistive devices What Where to find description detailed
  • 58. 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