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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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The company, product and service names used in this web site are for identification purposes only.
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Clinical decision system for GIST cancer - Presentation

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Presentation made by Alessandro Seganti during Semantic2015 Conference in Vienna.
Clinical decision support system application are a class of application to support physicians in their choice in treating patients. Cancer treatment is one of the area where CDSS applications can help physicians due to strict recommendations and the need for deciding if patients are eligible to enter clinical trial. To learn more, visit our website: http://www.cognitum.eu/

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Clinical decision system for GIST cancer - Presentation

  1. 1. 1 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Clinical decision support system for GIST Cancer Alessandro Seganti Data Engineer
  2. 2. 2 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Who we are : Cognitum  Fluent Editor  Ontorion Server  Ontorion Controlled Natural Language (OCNL)  Ask Your Data Anything (ADA)
  3. 3. 3 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Introduction Medical background, approach and challenges
  4. 4. 4 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Medical background  GIST cancer  Little known, High error rate  Well specified recommendations  Manage the long clinical history of the patient  Clinical trial
  5. 5. 5 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Requirements  Improve efficiency of treatment and quality of the data  No automatic decisions but recommendations  Use standard recommendations depending on the patient history  Keep the patient clinical history so that it can be reused
  6. 6. 6 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Next  Application architecture  Knowledge base  Reasoning  Live presentation
  7. 7. 7 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Application architecture
  8. 8. 8 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Application Architecture
  9. 9. 9 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. General idea Domain knowledge UI knowledge UI Generated knowledge
  10. 10. 10 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Knowledge base
  11. 11. 11 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Knowledge Modeling  How to model the long clinical history of a patient with GIST cancer.  Close collaboration with the domain expert  OCNL to write the ontologies that can be understood by the domain expert  SWRL for Rules.  Integrity Constraint rules for UI constraints.  Annotations for flexibility.
  12. 12. 12 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Histopathological report Patient basic information Surgery Follow up Medical Oncologist consultation Systemic therapy start Systemic therapy continue Systemic therapy stop Clinical trial
  13. 13. 13 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Automatic UI Generation
  14. 14. 14 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. UI generation - Structure Form Section Field
  15. 15. 15 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. UI generation - Fields Every patient must have-date (some datetime value).
  16. 16. 16 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. UI generation - Fields Every patient must have-age (some integer value). Every patient must have-sex a sex. Something is a sex if-and-only-if-it is either Male or Female.
  17. 17. 17 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Reasoning
  18. 18. 18 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Challenges  Reason efficiently and in a scalable way (independently on the number of patients).  Use knowledge dependent on time and reason over it.  Show recommendations based on the patient history.
  19. 19. 19 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Reasoning  Ontorion Server to store the knowledge base in a scalable way.  Modularization based on unique patient namespace.  Time dependent variables treated by having one instance at each point of time.  Only the latest instance is used for reasoning.  Reasoning using OWL-RL+ profile.
  20. 20. 20 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Reasoning: Transitions  If some condition on form-1 then form-1 is followed by another-form.  If some condition on section-1 inside form-1 then form-1 contains section-2.  SWRL statements.  Possible to use SWRL built-ins.
  21. 21. 21 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Recommendations  Recommendations coming from the ESMO guidelines.  Recommendations coming from good practices.  Modelled using SWRL rules.  Depending on the patient clinical history  Another rule is used to decide in which form the recommendation should be shown.
  22. 22. 22 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Live demonstration
  23. 23. 23 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Live Demonstration  Cdss  Other example of applications using Semantic Forms
  24. 24. 24 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Conclusions  Modeled medical knowledge base and applied it to build a complex web application supporting physicians in the daily work.  Innovative approach allowing for scalable reasoning independently on the number of patients.  Currently used in the Oncological center in Warsaw experimentally.  Currently working to apply the same approach to other type of cancer.
  25. 25. 25 The company, product and service names used in this web site are for identification purposes only. © Cognitum 2014. All trademarks and registered trademarks are the property of their respective owners. Thank you! Alessandro Seganti Data Engineer a.seganti@cognitum.eu Cognitum Sp. z o.o. Wal Miedzeszynski 630, Warsaw, Poland http://www.cognitum.eu/, office@cognitum.eu Windows Azure Circle Partner MEMBER

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