1. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 1 L&C’s LinkBase: a multi-lingual Hub to medical terminologies Dr. W. Ceusters Dir R&D Language & Computing nv

2. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 2 Presentation overview Short history of L&C L&C’s integrated approach to medical natural language understanding –Focus on medical terminology management Position in the international market Relevant demonstrations –LinkFactory –Ontology Browser

3. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 3 Goal of Language & Computing 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 hereby declare...

4. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 4 speech recognition TTS natural language understanding text generation Language Engineering speech text semantic representations language models semantic models dialogue models speech models information processing

5. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 5 The three pillars of Healthcare IT EHCRS Language Terminology Individual patient care Seamless care Historical overview... Comparability of data Crossborder care Decision support Abstraction / grouping... Faithful data recording Sufficient level of detail... Domain of discourse: healthcare

6. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 6 History of R&D in L&C AnthemMulti-TaleDomeGIUSelectC-CareLiquidMobidev R/D ratio

7. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 7 L&C’s integrated approach

8. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 8 The L&C integrated solution Data structure and function library for language understanding Medical and linguistic knowledge required for language understanding NLU enabling tools for knowledge supported data-entry and -retrieval

9. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 9 The L&C Linguistic Concept Factory Linguistic-semantic Function Library C-DEFINE(c-meningitis, c-inflammation HAS-LOC c-meninges) T-DEFINE(“méningite”, french, c-meningitis) Storage Functions Retrieval Functions GET-TERMS(c-meningitis, {french, dutch}) “méningite”, “hersenvliesontsteking”

10. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 10 Architectual overview

11. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 11 Client Graphical Objects

12. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 12 Build-in quality control Knowledge entered is immediately used to check validity of subsequent entries Version management User-management with : –Allowed actions based on experience –Personal audit trail Clear and formal separation with 3 rd party systems to avoid copying mistakes such as: –UMLS’ cyclical ISA relationships –SNOMED-RT ‘s “very usual = always” modelling –Most systems’ overloaded hierarchical relations

13. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 13 The L&C Linguistic Concept Database Formal Domain Ontology Lexicon Grammar Language A Lexicon Grammar Language B Cassandra Linguistic Ontology MEDRA ICD SNOMED ICPC Others... Proprietary Terminologies

14. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 14 A formal terminology Separation of terms and concepts To be used by machines, not people All information is explicit in the structure, not implicit in the terms Clean subsumption hierarchies Formal, “computable” definitions of concepts Internal, automated quality control

15. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 15 Expl: 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-OF joint 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

16. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 16 Expl: Relative spatial localisation IS- TOPO- INSIDE- OF IS-GEO- INSIDE- OF IS- INSIDE- CONVEX- HULL-OF IS-PARTLY- IN-CONVEX- HULL-OF IS- OUTSIDE- CONVEX- HULL-OF HAS- DISCONNECTED- REGION HAS- EXTERNAL- CONNECTING- REGION HAS-DISCRETED- REGION HAS- TANG.- SPAT.- PART HAS-NON- TANG.- SPAT.- PART IS- SPAT.- EQUIV.- OF IS- TANG.- SPAT.- PART-OF IS-NON- TANG.- SPAT.- PART-OF HAS- PARTIAL- SPATIAL- OVERLAP HAS- PROPER- SPATIAL -PART IS- PROPER- SPAT.- PART-OF HAS- SPATIAL -PART IS- SPATIAL -PART- OF HAS- OVERLAPPING -REGION HAS- CONNECTING- REGION HAS-SPATIAL- POINT- REFERENCE

17. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 17 Expl: Patient at risk (risk patient) 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 risk for osteoporosis Risk factor for osteoporosis Osteoporosis Has-Healthcare- phenomenon Is-Risk- Factor-Of IS-A 1 1 1 2 2 3 3 4 4

18. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 18 LinkBase size per 01-04-2001 920.000 (850.000) concepts 2.300.000terms 320link-types 2.000.000link instances 300.000links to 3 rd party systems But: –Never finished ! –Quality sufficient for current applications

19. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 19 Text ResultProcessor Domain representation Goal representation LinguisticKnowledge TaskKnowledge Formal domain ontology L&C Linguistic components Text ResultProcessor Domain representation Goal representation LinguisticKnowledge TaskKnowledge Formal domain ontology

20. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 20 L&C application servers Coding tools: FastCode Semantic indexers: Tessi Spell checkers and type ahead: FastType Semi controlled language parsers in restricted domains: FreePharma Ontology browser Stochastic dependency-based indexer: C-Link (Ir)relevant document classifier for very low prevalence data sets

21. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 21 FastCode Generator LinC- Factory Integrated coding approach Formal representation of Classification system LinCBase Mapping data Domain+Linguistic ontology FastCode client FastCode server Coding data

22. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 22 Benefits of formal multi-lingual terminology management

23. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 23 Semi-automatic mapping (ICPC-ICD10) Zenker’s diverticulum (D84) diverticulumesophagus HAS-LOC pressure HAS-CAUSEintraluminalHAS-ORIG Acquired diverticulum of esophagus (K22.5) HAS- LOC Acquired HAS-AcqMode HAS-AqMode

24. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 24 Reclassify: FOOT EXARTICULATION Definitions given by domain-expert: –( ( FOOT EXARTICULATION) { [ IS_A ] ( EXARTICULATION ) } { [HAS_THEME] ( FOOT ) } ) –( (AMPUTATION OF FOOT) { [ IS_A ] (AMPUTATION ) } { [ HAS_THEME ] ( FOOT ) } ) –( (EXARTICULATION) { [ IS_A ] (AMPUTATION ) } { [ HAS_SOURCE ] ( JOINT ) } ) Redefinition by automatic classifier –( ( FOOT EXARTICULATION ) –{ [ IS_A ] (AMPUTATION OF FOOT ) } –{ [ IS_A ] ( EXARTICULATION ) } )

25. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 25 Detection of missing terms

26. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 26 Resolving conflicting views MESH-2001 : “Seizures” MESH-2001 : “Convulsions” Snomed-RT : “Convulsion” Snomed-RT : “Seizure” L&C : ConvulsionL&C : Seizure L&C : Health crisis L&C : Epileptic convulsion IS-A IS-narrower-than ISA Has-CCC

27. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 27 Position in the market

28. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 28 Main business model Software developersIntegrators HospitalsInternet Service Providers Pharmaceutical companiesResearch Organisations Medical PublishersGovernment Healthcare Insurance CompaniesMCO

29. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 29 Project-based product development Service Component Product Component Project Definition Corpus analysis Set up service Product development Workbench development Teach and deliver

30. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 30 Current major partners/clients Coding tools –Several hospitals using ICD-9-CM FAstCode Terminology management services + NLU based data entry –IDEWE: largest Belgian occupational medicine services provider –First Databank UK –Belgian military medical service Semantic indexing –Belgian Professional Association of Pharmaceutical industry

31. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 31 Academic Competitors/Colleagues Main characteristics: –Prototypes with very small coverage –No professional support Relevant examples: –OpenGalen (VUMAN): Very small “LinkBase” “Toy”-link to language (language ignored as medium) –Protégé (Stanford): Ontology editor –Several DL-systems: FacT, Cyclop, LOOM,... Tested with very small (tiny) ontologies More powerful reasoning mechanisms than LinkFactory but totally intractable on ontologies of over a few 1000 distinct concept classes

32. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 32 Commercial competitors/colleagues Health Language Inc. Apelon Inc. –Ontyx –Lexical Technologies

33. L & C Dr. W. Ceusters Language & Computing nv www.landc.be 33 L&C’s strong position Multi-lingual and multi-cultural approach Modelling independent from specific languages but not from language as communication medium Proven scalability of our approach Support at all levels –Services to migrate existing client dictionairies –Large tool set for terminology development, maintenance, and/or use Only company with in-house expertise in medicine, computational linguistics in many languages, formal ontologies and informatics