ORC: an Ontology Reasoning Component for Diabetes

Transcription

1 ORC: an Ontology Reasoning Component for Diabetes Özgür Kafalı 1, Michal Sindlar 2, Tom van der Weide 2 and Kostas Stathis 1 1 Department of Computer Science Royal Holloway, University of London, UK {ozgur.kafali,kostas.stathis}@rhul.ac.uk 2 Portavita B.V., Netherlands {m.sindlar,t.van.der.weide}@portavita.eu August 3, 2013 Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

2 Outline 1 Introduction 2 COMMODITY 12 personal health system 3 ORC for semantic reasoning 4 Illustrative Example 5 Conclusions Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

3 Introduction Motivation Availability of medical data greatly increased data from different information sources and in different formats mediator-based integration approaches for data translation Build on the existing COMMODITY 12 framework for diabetes management Complement the integration process of the mediator with ontologies and semantic reasoning support Improve the existing logic-based agents that provide monitoring, advice and diagnosis Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

4 Introduction Contributions Study how to embed a semantic reasoning at the infrastructure level present SWRL rules to provide semantic reasoning on the ontology concepts instantiate the ontology with individuals coming from a patient database Describe a diabetic patient profile using an ontology formalised in OWL Profiles on diabetes not previously available Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

5 COMMODITY 12 personal health system COMMODITY 12 overview Management of diabetes becomes an increasingly important problem worldwide diabetic patients not able to take crucial decisions related to treatment need to consult healthcare professionals Advise patients with recommendations and alerts based on their data Assist medical personnel with taking informed and timely decisions Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

6 Architecture COMMODITY 12 personal health system Deductive, hypothetical and temporal reasoning + KB LAMA logical terms Translator Mediator Translator Translator Web interface XML Smart hub query processing Doctor Patient Patient DB Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

7 COMMODITY 12 personal health system Portavita interface Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

8 COMMODITY 12 personal health system LAMA agents Use personal agents [Kafalı et al. 2013] as active software components to manage specific characteristics of individuals in user profiles identify contextual conditions about the domain by observing through sensors process intelligently information by reasoning logically to support monitoring, the provision of alerts, advice, and diagnosis Use the agent platform GOLEM for deployment Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

9 Agent control COMMODITY 12 personal health system Mind Body Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

10 Agent control COMMODITY 12 personal health system Mind observations Body Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

11 Agent control COMMODITY 12 personal health system Mind observations call cycle step Body KB Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

12 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state Body KB Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

13 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body KB Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

14 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body KB activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

15 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body KB choose action activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

16 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body KB try action choose action activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

17 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body KB try action choose action activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

18 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body return KB try action choose action activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

19 Agent control COMMODITY 12 personal health system Mind observations call cycle step revise state select plan Body return KB execute action try action choose action activate goal Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

20 ORC for semantic reasoning COMMODITY 12 extended with ORC Existing COMMODITY 12 system Proposed extension Deductive, hypothetical and temporal reasoning + KB Ontology instance (individuals) Semantic rules (SWRL) Patient profile ontology (OWL) LAMA logical terms Translator Mediator Translator ontology individuals ORC import external ontologies Translator XML Web interface Smart hub query processing... Doctor Patient Patient DB Food SNOMED CT observation Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

21 Sample logic rule ORC for semantic reasoning a d v i s e e c o n s u l t a t i o n ( Patient, T): has age ( Patient, Age, T ), Age < 80, has no hospital access ( Patient, T ), \+ consulted ( Patient, i n t e r n i s t, years, 1, T ), h a s s y s t o l i c b p s ( Patient, [ MostRecent, SecondMostRecent Rest ], months, 6, T ), MostRecent > 140, SecondMostRecent > 140. Rule can be improved via semantic reasoning in terms of access to / inference on data: has no hospital access(...) inferred from living place Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

22 Sample logic rule ORC for semantic reasoning a d v i s e e c o n s u l t a t i o n ( Patient, T): has age ( Patient, Age, T ), Age < 80, has no hospital access ( Patient, T ), \+ consulted ( Patient, i n t e r n i s t, years, 1, T ), h a s s y s t o l i c b p s ( Patient, [ MostRecent, SecondMostRecent Rest ], months, 6, T ), MostRecent > 140, SecondMostRecent > 140. Rule can be improved via semantic reasoning in terms of access to / inference on data: has no hospital access(...) inferred from living place knowledge representation / development effort: has systolic bps(...) parent concept from class hierarchy Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

23 Ontology classes ORC for semantic reasoning Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

24 Ontology rules ORC for semantic reasoning Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

25 Illustrative Example Portavita patient database Patient Age Living Place Lutjebroek Patient Observation Date Code Value Portavita Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

26 Ontology assertions Illustrative Example f o r every p a t i e n t p : add to the ontology : i n d i v i d u a l p. p a t i e n t I d with class P a t i e n t P r o f i l e i n d i v i d u a l p. l i v i n g P l a c e with class LivingPlace o b j e c t p r o p e r t y p. p a t i e n t I d haslivingplace p. l i v i n g P l a c e o b j e c t p r o p e r t y p. p a t i e n t I d hasage p. age f o r every observation o : add to the ontology : i n d i v i d u a l o. o b s e r v a t i o n I d with class o. code d a t a p r o p e r t y o. o b s e r v a t i o n I d hasvalue o. value d a t a p r o p e r t y o. o b s e r v a t i o n I d hasmeasurementdate o. date o b j e c t p r o p e r t y o. p a t i e n t I d hasobservation o. o b s e r v a t i o n I d Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

27 Reasoning outcome Illustrative Example Get data from DB Apply semantic reasoning Translate ontology individuals into logic predicates has no hospital access ( patient 82319, ). h a s s y s t o l i c b p ( patient 82319, 133, ). h a s s y s t o l i c b p ( patient 82319, 141, ). h a s s y s t o l i c b p ( patient 82319, 157, ). Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17

28 Conclusions Conclusions Presented an ontology reasoning component ORC that: builds upon existing personal health environment COMMODITY 12 support the integration and interpretation of multimodal medical information Future work: integrate other ontologies such as for food and alcohol provide generic translators based on a concept ontology run experimental tests to evaluate our system Kafalı, Sindlar, van der Weide and Stathis ORC: Ontology Reasoning for Diabetes / 17