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Language, terminology andontology in a medical context:theory en reality inindustrial applications
Werner CEUSTERS
CTO
Language & Computing nv
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Presentation overview
1.L&C’s current key application
2.Some problems related to existing medicalterminology systems
3.Major reason: a too simplistic interpretation ofthe semantic/semiotic triangle
4.L&C’s answer: a cognitive approach toterminology connecting Aristotelian Realismwith Linguistic Functionalism
5.How this is implemented and used
6.Conclusions and issues for debate
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Mission of L&C nv
To provide
users and developers
of systems for
knowledge management
with tools and services
for efficient and accurate
data-entry and retrieval by
exploiting the full power of
automated (medical) natural
language understanding
We herebydeclare ...
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Anthem
Multi-Tale
Dome
GIU
Select
C-Care
Liquid
Mobidev
R/D ratio
Homey
Poirot
Inface
SCOP
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Most Successful Application
•Automatic semantic annotation of documents
–semantic indexing and retrieval
–relevance ranking of in-document semantics
–coding towards medical terminologies
•Often requires formalisation of clients’proprietary terminologies
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TeSSI Indexing Service
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TEX Indexing component
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Result 1 : Annotated document
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Result 2 : relevance ranking
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View on MeSH coding
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Behind the scene (1):Semantics based shallow processing
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Behind the scene (2): disambiguation
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But: this system is NOT perfect !
word not recognised
no code found in MeSH
missed the large syntactic scope of “infections”
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Some problems
Major problem:
most medical terminologies
are build following unsound principles
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ICD-10 “class-of” hierarchy
Problemareas:
1 2 3 4 5 6
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Problems of mapping
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Problems with naïve merging
UMLS
semanticdrift
ISA
circles
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UMLS
superficialtermanalysis
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Is a“formal”approachbetter ?SNOMED-RT
ISA ?
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Are these the only
problems ?
Don’t dream !
The semiotic/semantic triangle
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Language
Term
Symbol
Reality
Object
Concept – Model – Mind
“prototype” view
“characteristics” view
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•Normative interpretation (Wüster,ISO/TC37, prefered terms, ...)
•Too much focus on the concepts
•Assuming independence amongstthe vertices of the triangle
•Does not survive an intentional
framework
Where it went wrong ...
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Too much focus on the concepts
•“conceptualism” versus “realism”
•“ontology” versus “Ontology”
•oversimplification of reality
–discussions on 3D or 4D, instead of 3D and 4D
–limitations of set theory
•“independence of language” paradigm that doesnot accept language as a medium ofcommunication
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Triangular dependencies
concept
term
object
Baboons and humans have different cut-off points for discerning "same" objects becauseour verbal expression for "same" makes the idea of "same" more restrictive.”
Fagot and Wasserman (Centre for Research in Cognitive Neuroscience in Marseille)
Human observation is
determined by the
possibilities and
restrictions of the
human body.
Lakoff
The structures of language are
partially determined by our
conceptualisation of the
world.
Halliday
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Intentional framework problem
“I want to
go to ...”
“Brussels”“capital of Belgium”
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The basis of L&C’s approach
Aristotelian
realism
Halliday’s systemic
functional
grammar
Natural Language
Understanding for
(medical)
reality
the description of
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LinkBase
Formal DomainOntology
Lexicon
Grammar
Language ALanguage A
Lexicon
Grammar
Language BLanguage B
Cassandra LinguisticOntology
MEDDRA
ICD
SNOMED
ICPC
Others ...
Proprietary Terminologies
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Example: joint anatomy
•joint HAS-HOLE joint space
•joint capsule IS-OUTER-LAYER-OF joint
•meniscus
–IS-INCOMPLETE-FILLER-OF joint space
–IS-TOPO-INSIDE joint capsule
–IS-NON-TANGENTIAL-MATERIAL-PART-OFjoint
•joint
–IS-CONNECTOR-OF bone X
–IS-CONNECTOR-OF bone Y
•synovia
–IS-INCOMPLETE-FILLER-OF joint space
•synovial membrane IS-BONAFIDE-BOUNDARY-OF joint space
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Linguistic and domain ontologies
Having a healthcare phenomenon
Generalised Possession
Healthcare phenomenon
Human
IS-A
Has-
possessor
Has-
possessed
Patient
Is-possessor-of
Patient at risk
IS-A
Has-Healthcare-phenomenon
Risk Factor
IS-A
Is-Risk-
Factor-Of
Patient at riskfor osteoporosis
Risk factor forosteoporosis
Osteoporosis
Has-Healthcare-phenomenon
Is-Risk-
Factor-Of
IS-A
IS-A
IS-A
1
1
1
2
2
IS-A
3
3
4
4
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The industrial challenge
•How to set up a profitable business taking intoaccount
–the problems intrinsic to medical terminologies
•the obligation for many clients to use them
•the existence of many different, incompatible systems
•often based on a design that is not suited for automaticprocessing
–the problems intrinsic to natural language processing
–the business environment in which our applicationshave to run
–the high costs for “doing right what others do wrong”
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production
maintenance
research
Integration of Research, maintenance and production
corrected
document
gold standard corpus
text to analyse
client
document set
candidate
knowledge
gap
WWW
“WebAgent”
“GapFinder”
new-terms
various beans
candidate
classified
terms
“Model-H1”
various beans
marked up text
Medico-Linguistic
Ontology
TeSSI, ...
relevancerankingindex
uncorrected
document
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A terminological workbench formaintenance AND production!
The
solution
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LinkFactory ToolSet
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Managing different views
Externalontology
Internalontology
Criteria
Mappings
Definitions
Terms
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Assisted term classification
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Gap-Finder andWeb-Agent
1.concept queried for
2.information used for documentrelevance assessment
3.new words retrieved
4.context-information for newword
5.relevant pages found
1
2
3
4
5
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Research:automatic ontology extraction
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Some details
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Conclusions (and issues for discussion)
1.Medical natural language understanding (MNLU) is avery complex endeavour;
2.Terminology is a necessary component, though not themost important one;
3.Traditional terminology approaches have less valuefor MNLU than those that accept a close relationshipwith language and reality (e.g. the “sociocognitive” approach);
4.Some traditional, authoritative sources in medicalterminology follow a wrong approach;
5.Get away with Conceptualism and adopt Realism.
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Successful industrial application ofMNLU requires (amongst other things):
1.Acceptation of the previous points withoutdiscussion;
2.200% awareness of the state of the art;
3.the capacity to make valid judgments about theexpected outcomes of a (new) theory withoutrequiring full proofs;
4.an integrated service/production andmaintenance/ development environment totransform costs into revenue.