SLIDE 1
Describing Localized Diseases in Medical Ontology: An FMA-based Algorithm
Jean Charlet1,2, Laurent Mazuel1,7, Gunnar Declerck2, Patrick Miroux5, Pierre Gayet6
1- AP-HP, Paris, France; 2- INSERM, U1142, LIMICS, 75006, Paris, France, Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, 75006, Paris, France, Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), 93430, Bobigny, France; 3- Antidot, Lambesc, France; 4- Costech, Université de Technologie de Compiègne, Compiègne, France; 5- Dpt Urgences CHU Angers, France; 6- Centre hospitalier de Compiègne, France; jean.charlet@upmc.fr
MIE 2014, Istanbul, September 1, 2014
SLIDE 2 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
1
An Information Retrieval Ontology Lerudi
2
Pathophysiology vs Anatomy Modelization Problem Objective Material
3
Algorithm
4
Result
5
Discussion
6
Perspectives
Jean Charlet et al. MIE2014
SLIDE 3
ONTOLURGENCES: An information retrieval ontology
In the context of the LeRUDI project Give physicians a GUI to facilitate the quick reading of the EHR for emergency care practitioners (mainly textual) Provide an overview of the patient in less than 2 mins Previous version (without FMA algorithm) available at
http://purl.oclc.org/NET/spim/ontologies/public/ OntolUrgences/
A TOR, Terminological and Ontological Resource Identify concepts in the medical texts Thanks to terms denoting the concepts In order to reason about conceptual structures Thanks to “is-a” relation In order to display, among others, medical specialties in a concept cloud
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Algorithm Result Discussion Perspectives Addendum
LeRUDI: Research screen
Jean Charlet et al. MIE2014
SLIDE 5 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
'maladie du tube digestif' 'maladies de l'intestin grèle et du gros intestin' appendicite
has subclass
'maladie du tube digestif global'
has subclass
chirurgie
estUneMaladieDeLaSpecialiteMedicale(Subclass some)
'maladies de l'appendice'
has subclass
'maladie inflammatoire localisee'
has subclass
'cancer intestinal'
has subclass
'maladie du rectum'
has subclass
'maladie abdominale'
has subclass
'maladie du mésentère'
has subclass
'maladies de l'oesophage, de l'estomac et du duodénum'
has subclass has subclass
gastro-entérologie
estUneMaladieDeLaSpecialiteMedicale(Subclass some)
'occlusion digestive'
has subclass
'maladie du côlon'
has subclass
Jean Charlet et al. MIE2014
SLIDE 6 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
LeRUDI: Pathophysiology and anatomy (2/3)
Pathophysiological and anatomical points of view play a key role in the characterization of medical pathologies The work of building a medical ontology must integrate and explicitly model them However, significant challenges had to be tackled in order to successfully achieve the modeling In addition, ensuring logical as well as semantic consistency when modeling both points of view added to this complexity
Jean Charlet et al. MIE2014
SLIDE 7 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
LeRUDI: Pathophysiology and anatomy (3/3)
Pathophysiology is the main axis of description of complex patients Pathophysiology is less well controlled than anatomy In most cases, pathophysiological position of a disease is unique while anatomical position is multiple (e.g. bronchopneumopathy) Develop the pathophysiological axis of the ontology and reuse a reference resource, the Foundational Model of Anatomy (FMA), to construct the localized diseases axis
Jean Charlet et al. MIE2014
SLIDE 8 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Objective
1
Organize all the concepts of diseases in a tree representing the pathophysiological perspective as understood by emergency medicine – e.g. CardiacAneurism is-a aneurism
2
Develop Branch of localized diseases with defined concepts (in order to position concepts defined in (1) through automatic classification). This requires:
Define localization axioms – e.g. heart disease is on heart (and, if necessary only on heart) –, and Develop branch of anatomy necessary for the expression of the previous axioms – e.g. the heart itself: Heart is-a OrganWithCavitatedOrganParts.
Jean Charlet et al. MIE2014
SLIDE 9 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Used Resources
Ontolurgences v3.03. 10,191 classes, 60 Object Properties, 1 Data properties, and 11,591 logical axioms including 11,339 subclass axioms, and 89 equivalent class
- axioms. OntolUrgences is built with core-ontology
OntoMénélas1. The FMA. (Foundational Model of Anatomy) a reference
- ntology about human anatomy. 85,000 classes, 140
relationships connecting the classes, and more than 120,000 terms. We used the FMA v3.2.1 in OWL Full.
1http://purl.oclc.org/NET/spim/ontologies/public/OntoMenelas/ Jean Charlet et al. MIE2014
SLIDE 10 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Algorithm - 0
Annotation for Localization by medical practitioners Annotation of concepts of the ontology by an FMA identifier
Possibility of AND (bronchopneumopathy is disease of the bronchi AND the lung)
Jean Charlet et al. MIE2014
SLIDE 11 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Algorithm - 1
Copying an extract of the FMA For each concept with an annotation onto:pourFMA (step 0), we copy concepts used in the annotation and all its relative superclasses to
fma:Physical_anatomical_entity
Built branch is stored under onto:StructureAnatomique (i.e. anatomical structure) which is a class of OntoMénélas core-ontology Conservation of FMA URIs
Jean Charlet et al. MIE2014
SLIDE 12 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Algorithm - 2 I
Principle If 2 concepts are in meronymic relationships (part-whole), localized associated diseases are in subsumption relationships – e.g. “The mitral valve is a part of the heart” implies “the mitral valve disease is a heart disease”
Jean Charlet et al. MIE2014
SLIDE 13 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Algorithm - 2 II
Creation of diseases hierarchy Given a concept X, if it has a relationship part_of to concept Y, then create the concept DiseaseOfY as father
At each iteration, use one relation part_of, in order of preference systemic_part_of
constitutional_part_of, then regional_part_of,
To ensure the final connectivity of the graph, if the concept has no relation part_of, then follow the classical subsumption relationship
Jean Charlet et al. MIE2014
SLIDE 14
Algorithm - 3
Localization definition by Defined Concepts
EquivalentClass(onto:DiseaseOfLung ObjectIntersectionOf(onto:DiseaseOfLowerRespiratoryTract ObjectSomeValuesFrom(onto:localizedOn fma:Lung) ObjectAllValuesFrom(onto:localizedOn fma:Lung)))
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Algorithm Result Discussion Perspectives Addendum
Result
Result: a new ontology 12,396 Classes, 60 Object Properties, 1 Data property and 17072 axioms, among them, 13332 subclass axioms and 3559 equivalent classes axioms Compare the last number to 89 equivalent classes axioms in the previous version Incrementality The algorithm is incremental. It is not necessary to keep a pre-algorithm version in order to apply it several times
Jean Charlet et al. MIE2014
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Algorithm Result Discussion Perspectives Addendum
Discussion I
Evaluation Evaluation of this work is done in-house and is used to improve the presented algorithm About FMA bugs During the development, this work uncovers FMA (small)
- mistakes. The FMA team corrects them
Jean Charlet et al. MIE2014
SLIDE 17 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Discussion II
French vs English terms During the development of the algorithm, we work in English, because FMA is mainly in English. We collaborate with the FMA team and CISMeF in order to enrich the FMA with French terms (around 15,000)
Jean Charlet et al. MIE2014
SLIDE 18 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
Perspectives I
Which part_of? The systemic point of view seemed the more understandable for the practitioner, because it corresponds to a partitioning of medicine into medical specialties. But the FMA team deleted
systemic_part_of due to its lack of coherence. We need to
make new tests using, in order of preference,
constitutional_part_of then regional_part_of
About complexity of created ontology The resulting ontology is very complex. We investigate the possibility of reducing the visibility of some concepts (or deleting them) in the ontology
Jean Charlet et al. MIE2014
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Algorithm Result Discussion Perspectives Addendum
Perspectives II
About onto:pourFMA Need to have annotations which point to “more” systemic anatomy elements Current work: re-localization of 2,000 concepts in order to correspond to medical specialties New annotation onto:pourFMAO in order to better take into account the localization on X OR Y
Jean Charlet et al. MIE2014
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Algorithm Result Discussion Perspectives Addendum
Perspectives III
Last FMA version New FMA without systemic_part_of available on Bioportal Result Give access to the new ontology before the end of the year on Bioportal
Jean Charlet et al. MIE2014
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Algorithm Result Discussion Perspectives Addendum
Thank you for your attention. . .
Jean Charlet et al. MIE2014
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Algorithm Result Discussion Perspectives Addendum
LeRUDI: un projet terminé (2009-2012) et évalué (1/2)
ASIP-santé : ICS-CISMEF-LERTIM-Sword-Antidot-MONDECA-ARISEM
Jean Charlet et al. MIE2014
SLIDE 23 An I.R. Ontology
Algorithm Result Discussion Perspectives Addendum
LeRUDI: un projet terminé (2009-2012) et évalué (2/2)
ASIP-santé : ICS-CISMEF-LERTIM-Sword-Antidot-MONDECA-ARISEM
Jean Charlet et al. MIE2014
SLIDE 24
Processus versus localisation I
SLIDE 25
Processus versus localisation II
