1. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics IADR Satellite Symposium Ontology: Innovative Approach to Orofacial Pain Classification March 19, 2013 – Washington State Convention Center, Seattle, WA Werner CEUSTERS, MD Center of Excellence in Bioinformatics and Life Sciences, Ontology Research Group, Institute for Healthcare Informatics, Department of Psychiatry University at Buffalo, NY, USA http://www.org.buffalo.edu/RTU

2. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics A classification of animals Those that belong to the emperor Embalmed ones Those that are trained Suckling pigs Mermaids (or Sirens) Fabulous ones Et cetera Those that are included in this classification 2 Those that tremble as if they were mad Innumerable ones Those drawn with a very fine camel hair brush Stray dogs Those that have just broken the flower vase Those that, at a distance, resemble flies Jorge Luis Borges. The Analytical Language of John Wilkins. 1942. (Selected nonfictions, Eliot Weinberger, transl., Penguin Books, p. 231, ISBN 0-14-029011-7) Celestial Emporium of Benevolent Knowledge's Taxonomy

3. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics A classification of animals Those that belong to the emperor Embalmed ones Those that are trained Suckling pigs Mermaids (or Sirens) Fabulous ones Et cetera Those that are included in this classification 3 Those that tremble as if they were mad Innumerable ones Those drawn with a very fine camel hair brush Stray dogs Those that have just broken the flower vase Those that, at a distance, resemble flies Jorge Luis Borges. The Analytical Language of John Wilkins. 1942. (Selected nonfictions, Eliot Weinberger, transl., Penguin Books, p. 231, ISBN 0-14-029011-7) Celestial Emporium of Benevolent Knowledge's Taxonomy Ridiculous?

4. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 4 Geographic Locations [Z01] in MESH Africa [Z01.058] + Americas [Z01.107] + Antarctic Regions [Z01.158] Arctic Regions [Z01.208] Asia [Z01.252] + Atlantic Islands [Z01.295] + Australia [Z01.338] + Cities [Z01.433] + Europe [Z01.542] + Historical Geographic Locations [Z01.586] + Indian Ocean Islands [Z01.600] + Oceania [Z01.678] + Oceans and Seas [Z01.756] + Pacific Islands [Z01.782] + Ancient Lands [Z01.586.035] + Austria-Hungary [Z01.586.117] Commonwealth of Independent States [Z01.586.200] + Czechoslovakia [Z01.586.250] + European Union [Z01.586.300] Germany [Z01.586.315] + Korea [Z01.586.407] Middle East [Z01.586.500] + New Guinea [Z01.586.650] Ottoman Empire [Z01.586.687] Prussia [Z01.586.725] Russia (Pre-1917) [Z01.586.800] USSR [Z01.586.950] + Yugoslavia [Z01.586.980] + ? ? ?

5. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 5 MeSH: some paths from top to Wolfram Syndrome Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Diseases Optic Atrophy Optic Atrophies, Hereditary Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus Female Urogenital Diseases and Pregnancy Complications Female Urogenital Diseases

6. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 6 What would it mean if used in the context of a patient ? Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Diseases Optic Atrophy Optic Atrophies, Hereditary has Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Female Urogenital Diseases and Pregnancy Complications Female Urogenital Diseases Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus ??? … has

7. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Ridiculous ? Those that belong to the emperor Embalmed ones Those that are trained Suckling pigs Mermaids (or Sirens) Fabulous ones Et cetera Those that are included in this classification 7 Celestial Emporium of …Pain classification Peripheral Neuropathy (I-1) 203.X2a Arms: infective 203.X3a Arms: inflammatory or immune reactions 203.X5a Arms: toxic, metabolic, etc. 203.X8a Arms: unknown or other 603.X2a Legs: infective 603.X3a Legs: inflammatory or immune reactions 603.X5a Legs: toxic, metabolic, etc. 603.X8a Legs: unknown or other X03.X4d Von Recklinghausen's disease

8. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Why ridiculous? Non-systematic criteria. reference to external characteristic not animal anymore temporal characteristic do not exist at all ambiguous open ended reference to observer 8 Those that belong to the emperor Embalmed ones Those that are trained Suckling pigs Mermaids (or Sirens) Fabulous ones Et cetera Those that are included in this classification Those that, at a distance, resemble flies

9. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics A first stab at systematization: Terminology 9 7 criteria for a good term: –Transparency: to make the term transparent, a delimiting characteristic is used to create the term –Consistency: within a concept system –Appropriateness: adhere to establish patterns, avoid confusion –Linguistic economy –Derivability –Compoundability –Linguistic correctness –Preference for native language. ISO 704, 2000

10. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Application in healthcare: Cimino’s desiderata 10

11. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics The weakness of terminology 11 7 criteria for a good term: –Transparency: to make the term transparent, a delimiting characteristic is used to create the term –Consistency: within a concept system –Appropriateness: adhere to establish patterns, avoid confusion –Linguistic economy –Derivability –Compoundability –Linguistic correctness –Preference for native language. ISO 704, 2000

12. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics The wobbly foundations of concept theories 12

13. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics A better way to systematize: ‘Ontology’ In philosophy: –Ontology (no plural) is the study of what entities exist and how they relate to each other; –by some philosophers taken to be synonymous with ‘metaphysics’ while others draw distinctions in many distinct ways (the distinctions being irrelevant for this talk), but almost agreeing on the following classification: metaphysics  studies ‘how is the world?’ –general metaphysics  studies general principles and ‘laws’ about the world »ontology  studies what type of entities exist in the world –special metaphysics  focuses on specific principles and entities –distinct from ‘epistemology’ which is the study of how we can come to know about what exists. –distinct from ‘terminology’ which is the study of what terms mean and how to name things.

14. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics A better way to systematize: ‘Ontology’ In philosophy: –Ontology (no plural) is the study of what entities exist and how they relate to each other; In computer science and many biomedical informatics applications: –An ontology (plural: ontologies) is a shared and agreed upon conceptualization of a domain;

15. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Semantic Applications use Computer science approach to ontology 15 Ontology Authoring Tools Reasoners create Domain Ontologies

16. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Semantic Applications use Computer science approach to ontology 16 Ontology Authoring Tools Reasoners create Domain Ontologies the logic in reasoners: guarantees consistent reasoning, does not guarantee the faithfulness of the representation.

17. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 17 Consistent reasoning with nonsensical representations Ceusters W, Smith B, Flanagan J. Ontology and Medical Terminology: why Descriptions Logics are not enough. Proceedings of the conference Towards an Electronic Patient Record (TEPR 2003), San Antonio, 10-14 May 2003 (electronic publication 5pp)

18. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Philosophical approach to ontology 18 Ontological Realism: uses ontology as philosophical discipline to build ontologies as faithful representations of reality.

19. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics

20. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 1.There is an external reality which is ‘objectively’ the way it is; 2.That reality is accessible to us; 3.We build in our brains cognitive representations of reality; 4.We communicate with others about what is there, and what we believe there is there. The basis of Ontological Realism (O.R.) Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

21. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Ontology  Terminology 21 reality language knowledge

22. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Ontological Realism makes three crucial distinctions 1.Between data and what data are about; 2.Between continuants and occurrents; 3.Between what is generic and what is specific. 22 Smith B, Ceusters W. Ontological Realism as a Methodology for Coordinated Evolution of Scientific Ontologies. Applied Ontology, 2010;5(3-4):139-188.

23. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics L1 - L2 L3 23 Linguistic representations about (L1 - ), (L2) or (L3) Beliefs about (1) Entities (particular or generic) with objective existence which are not about anything Representations First Order Reality

24. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics L1/L2/L3 and pain IASP definition for ‘pain’: –‘an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage’; what asserts: –a common phenomenology (‘unpleasant sensory and emotional experience’) to all instances of pain, –the recognition of three distinct subtypes of pain involving, respectively: 1.actual tissue damage, 2.what is called ‘potential tissue damage’, and 3.a description involving reference to tissue damage whether or not there is such damage.

25. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Between ‘generic’ and ‘specific’ L1. First-order reality L2. Beliefs (knowledge) GenericSpecific DIAGNOSIS INDICATION my doctor’s work plan my doctor’s diagnosis MOLECULE PERSON DISEASE PATHOLOGICAL STRUCTURE MIGRAINE HEADACHE DRUG me my headache my migraine my doctor my doctor’s computer L3. Representation pain classification EHR ICHDmy EHR Referent TrackingBasic Formal Ontology GenericSpecific 25

26. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics etiological processdisorderdiseasepathological process abnormal bodily featuressigns & symptomsinterpretive processdiagnosis producesbearsrealized_in producesparticipates_inrecognized_as produces Example: Ontology of General Medical Science (OGMS) http://code.google.com/p/ogms/ Scheuermann R, Ceusters W, Smith B. Toward an Ontological Treatment of Disease and Diagnosis. 2009 AMIA Summit on Translational Bioinformatics, San Francisco, California, March 15-17, 2009;: 116-120. http://www.referent-tracking.com/RTU/sendfile/?file=AMIA-0075-T2009.pdf

27. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics No conflation of diagnosis, disease, and disorder The disorder is thereThe diagnosis is here The disease is there

28. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Some principles for O.R.-based classifications P1: Be explicit whether assertions are about particulars or types P2: Be precise about the sort of particulars to be classified using the classification P3: Particulars that correctly can be classified at a certain class level, and thus are instances of the corresponding type, should also be instance of all the types that correspond with higher level classes. P4: Keep knowledge separate from what the knowledge is about. P5: Class descriptions should be consistent with class labels. P6: Use Aristotelian definitions. P7: Clinical criteria do not replace Aristotelian definitions. 28 Are all violated in new (draft of?) Chapter 13 of ICHD

29. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P1) Are assertions about particulars or types? ‘Persistent idiopathic facial pain (PIFP)’ = ‘persistent facial pain with varying presentations …’ 29 t1t1 t2t2 t3t3 t1t1 t2t2 t3t3 t1t1 t2t2 t3t3 t1t1 t2t2 t3t3 t1t1 t2t2 t3t3 t1t1 t2t2 t3t3 persistent facial pain presentation type1 presentation type3 presentation type2 types my painhis painher pain parti- culars

30. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P1) Are assertions about particulars or types? ‘Persistent idiopathic facial pain (PIFP)’ = ‘persistent facial pain with varying presentations …’ –if the description is about types, then the three particular pains fall under PIFP. –if the description is about (arbitrary) particulars, then only her pain falls under PIFP. 30

31. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P2) Sort of particulars to be classified What is classified in ICHD? –disorders? ‘The International Classification of Headache Disorders’ –headaches? ‘ Many questions not needed in order to classify primary headaches…’ –patients? ‘The second edition will hopefully further promote unity in the way we classify, diagnose and treat headache patients throughout the world.’ –palsies? –syndromes? 31 can be assumed from some heading names

32. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P3) Maintain a strict subsumption hierarchy 13.1. Trigeminal Neuralgia –13.1.2 Painful Trigeminal Neuropathy ICHD definitions: 1.‘neuralgia’ = pain in the distribution of nerve(s) 2.‘pain’ = a sensorial and emotional experience... 3.‘neuropathy’ = a disturbance of function or pathological change in a nerve. Several mismatches: –(1) and (2): neuralgia is a sensorial and emotional experience in the distribution of nerve(s) ? –(1) and (3): with much of goodwill, one could accept neuropathy to subsume neuralgia, but chapter 13 claims the opposite for the trigeminal case. 32 subsumes?

33. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 33 P3-related mistake: false synonymy in SNOMED nose bones fracture

34. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 34 Coding / Classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = =

35. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics 35 A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = = Coding / Classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = =

36. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P4) Separate knowledge from what it is about. ‘13.1.2.4 Painful trigeminal neuropathy attributed to MS plaque’ ‘attributed to’ relates to somebody’s opinion about what is the case, not to what is the case. –the mistake: a feature on the side of the clinician – his (not) knowing - is taken to be a feature on the side of the patient. Similar mistakes: –‘Probable migraine’ –‘facial pain of unknown origin’ (not in ICHD). 36

37. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P5) Class descriptions should be consistent with class labels ‘13.1.2.4 Painful Trigeminal neuropathy attributed to MS plaque’: –described as ‘Trigeminal neuropathy induced by MS plaque’. attributed  induced reference to pain missing in the description 37

38. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P6) Use Aristotelian definitions. A B isa A which X C isa B which Y D isa C which Z Make sure that X holds for C and that both X and Y hold for D. Use this also in label formation to prevent, f.i., –‘13.3 Nervus Intermedius (Facial Nerve) Neuralgia’ ‘13.3.2. Secondary Nervus Intermedius Neuropathy attributed to Herpes Zoster’ 38

39. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics (P7) Clinical criteria do not replace Aristotelian definitions ‘13.1.1.1 Classical trigeminal neuralgia, purely paroxysmal’, has the criterion ‘at least three attacks of facial pain fulfilling criteria B-E’. This does not mean: a patient with 2 such attacks does not exhibit this type of neuralgia; It rather means: do not diagnose the patient (yet) as exhibiting this type of neuralgia. If ‘chronic pain’ is defined as ‘pain lasting longer than three months’, at what point in time starts a patient to have that type of pain? 39

40. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Conclusion Realism-based ontology has a lot to offer to build faithful representations. It is hard ! Pain classifications, and as thus far ALL OTHER classifications made by domain experts, would benefit from it. –domain experts are not ontologists. Old habits, main stream thinking, and guru-ism hamper the advance of science.

41. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Institute for Healthcare Informatics Acknowledgement The work described is funded in part by grant 1R01DE021917-01A1 from the National Institute of Dental and Craniofacial Research (NIDCR). The content of this presentation is solely the responsibility of the author and does not necessarily represent the official views of the NIDCR or the National Institutes of Health.