Bamidis, P. et al.: Usage of Semantic Web Technologies (Web 3.0) Aiming to Facilitate the Utilisation of Computerized Algo...
Charalampos Bratsas,  Panagiotis Bamidis  *, Evangelos Kaimakamis, Nicos Maglaveras  Lab of Medical Informatics,  Medical ...
Outline <ul><li>Definition of Medical Computational Problems and the benefits of use algorithms in Medicine  </li></ul><ul...
Medical   Computational Problems  –  Computerized Algorithmic Solutions <ul><li>Medical Computational Problems   MCPs: Med...
Conclusions of MIE 2006 Workshop <ul><li>There are tens of thousands of algorithms. </li></ul><ul><li>They are not widely ...
Conclusions of MIE 2006 Workshop <ul><li>Why aren’t algorithms used?  </li></ul><ul><ul><li>I don’t have the time. </li></...
Main reason -Solution  Structure Framework to describe MCPs     Ontologies Structure and Education C Bratsas,  P Bamidis ...
Scope - Solutions <ul><li>Develop  the semantic framework (MCP Ontology]) enclosing the required knowledge based on which ...
MCP Ontology <ul><li>The MCP Ontology is an OWL ontology model that manages MCPs and their solutions by means of organizin...
MCP Ontology Model  <ul><li>Ontologies  : </li></ul><ul><ul><li>Medical Problem Ontology </li></ul></ul><ul><ul><li>Medica...
<ul><li>Adaptation of the classical Vector Space Model  ( VSM )  in MCP Ontology based on which </li></ul><ul><ul><ul><li>...
MCP Ontology - Managing a certain medical case   <ul><ul><li>Dynamic semantic composition of a sequence of algorithms </li...
KnowBaSICS-M Modular Architecture
KnowBaSICS-M Technical Architecture Diagram <ul><li>Code development was based on open-source development platforms and to...
Experimental evaluation   -  Goals <ul><li>To evaluate KnowBaSICS-M either for knowledge insertion or for knowledge retrie...
Evaluation Process C Bratsas,  P Bamidis *, E Kaimakamis, N Maglaveras
Experimental Results Similarity Similarity C Bratsas,  P Bamidis *, E Kaimakamis, N Maglaveras New MCPs Satisfy Answer
Experimental Results of Search  Precision Recall  harmonic mean   C Bratsas,  P Bamidis *, E Kaimakamis, N Maglaveras
Test Case 1. Search similar MCP: Treatment of massive pulmonary embolism2. Find Algorithmic Sequence   to manage a specifi...
Future Research  <ul><li>Major technical challenge is the automated incorporation of the content located at existing repos...
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Usage of Semantic Web Technologies (Web 3.0) Aiming to Facilitate the Utilisation of Computerized Algorithmic Medicine in Clinical Practice [Med2 Bratsas V2]

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  • Usage of Semantic Web Technologies (Web 3.0) Aiming to Facilitate the Utilisation of Computerized Algorithmic Medicine in Clinical Practice [Med2 Bratsas V2]

    1. 1. Bamidis, P. et al.: Usage of Semantic Web Technologies (Web 3.0) Aiming to Facilitate the Utilisation of Computerized Algorithmic Medicine in Clinical Practice <ul><li>This slideshow, presented at Medicine 2.0’08 , Sept 4/5 th , 2008, in Toronto, was uploaded on behalf of the presenter by the Medicine 2.0 team </li></ul><ul><li>Do not miss the next Medicine 2.0 congress on 17/18th Sept 2009 ( www.medicine20congress.com ) </li></ul><ul><li>Order Audio Recordings (mp3) of Medicine 2.0’08 presentations at http://www.medicine20congress.com/mp3.php </li></ul>
    2. 2. Charalampos Bratsas, Panagiotis Bamidis *, Evangelos Kaimakamis, Nicos Maglaveras Lab of Medical Informatics, Medical School Aristotle University of Thessaloniki Usage of Semantic Web Technologies (Web-3.0) Aiming to Facilitate the Utilisation of Computerized Algorithmic Medicine in Clinical Practice
    3. 3. Outline <ul><li>Definition of Medical Computational Problems and the benefits of use algorithms in Medicine </li></ul><ul><li>Why algorithmic medicine doesn't used? What is the main problem? </li></ul><ul><li>Scope – Solutions </li></ul><ul><li>Ontologies as a structure framework of MCPs </li></ul><ul><li>Methods and Web-System architecture (KnowBaSICS-M) </li></ul><ul><li>Experimental evaluation and test case </li></ul><ul><li>Future research </li></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    4. 4. Medical Computational Problems – Computerized Algorithmic Solutions <ul><li>Medical Computational Problems MCPs: Medical problems, the solution of which deals with mathematical or statistical models, signal or image processing and estimation of corresponding parameters . </li></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras To define MCPs and their solutions different domains of knowledge are required Collaboration of different kind of scientists .
    5. 5. Conclusions of MIE 2006 Workshop <ul><li>There are tens of thousands of algorithms. </li></ul><ul><li>They are not widely incorporated into routine care. </li></ul><ul><li>We believe that healthcare would be better if they were. </li></ul><ul><li>Ontology support for Algorithmic Medicine </li></ul>John R Svirbely, Jan Vejvalka, M Sriram Iyengar, Charalampos Bratsas, Evangelos Kaimakamis, Nicos Maglaveras. Technological guidelines for integrating medical algorithms into healthcare systems C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    6. 6. Conclusions of MIE 2006 Workshop <ul><li>Why aren’t algorithms used? </li></ul><ul><ul><li>I don’t have the time. </li></ul></ul><ul><ul><li>I didn’t know there was one. </li></ul></ul><ul><ul><li>I don’t remember what it is. </li></ul></ul><ul><ul><li>I don’t have a software. </li></ul></ul><ul><ul><li>I don’t have the data I need. </li></ul></ul><ul><ul><li>I don’t know how to use it. </li></ul></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras John R Svirbely, Jan Vejvalka, M Sriram Iyengar, Charalampos Bratsas, Evangelos Kaimakamis,Nicos Maglaveras. Technological guidelines for integrating medical algorithms into healthcare systems
    7. 7. Main reason -Solution Structure Framework to describe MCPs  Ontologies Structure and Education C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras Doctors, Mathematicians, Physics , etc Informatics
    8. 8. Scope - Solutions <ul><li>Develop the semantic framework (MCP Ontology]) enclosing the required knowledge based on which the medical problem - algorithm - implementation are semantically described. </li></ul><ul><li>Develop knowledge retrieval methods, through ontological questions and the utilization of information retrieval methods inside the MCP Ontology. </li></ul><ul><li>Develop dynamic semantic composition of a sequence of algorithms managing a certain medical case </li></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras Scope: The initial development of semantic descriptions of Medical Computational Problems (MCPs) and the management of resulting knowledge.
    9. 9. MCP Ontology <ul><li>The MCP Ontology is an OWL ontology model that manages MCPs and their solutions by means of organizing and visualizing their existing knowledge. </li></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    10. 10. MCP Ontology Model <ul><li>Ontologies : </li></ul><ul><ul><li>Medical Problem Ontology </li></ul></ul><ul><ul><li>Medical Algorithm Ontology </li></ul></ul><ul><ul><li>Implementation Ontology </li></ul></ul><ul><ul><li>Users Ontology </li></ul></ul><ul><li>Reuses or/and Adaptations : </li></ul><ul><li>BibTex Ontology to semantically describe the MCPs References ( http://www.cs.toronto.edu/semanticweb/maponto/ontologies/BibTex.owl ) </li></ul><ul><li>UMLS Ontology to semantically describe the medical concepts. ( Unified Medical Language System ) ( http:// umlsks.nlm.nih.gov / kss ) </li></ul><ul><li>ConOnto Ontology to semantically describe the software and hardware of implemented algorithm ( http:// www.site.uottawa.ca/~mkhedr/Ontologies / ) </li></ul><ul><li>Global Medical Device Nomenclature to semantically describe the medical devices ( http:// www.gmdnagency.com / ) </li></ul>
    11. 11. <ul><li>Adaptation of the classical Vector Space Model ( VSM ) in MCP Ontology based on which </li></ul><ul><ul><ul><li>The MCP weighted vectors are created by the implementation of the weights of the UMLS terms acting as the problem indexing terms in the MCP Ontology </li></ul></ul></ul><ul><ul><ul><ul><li>tf factor: based on the frequency of occurrence of the instances of a keyword (UMLS concept) into MCPs natural language description </li></ul></ul></ul></ul><ul><ul><ul><ul><li>idf factory: based on frequency of occurrence of the instances of a keyword (UMLS concept) into MCP Ontology. </li></ul></ul></ul></ul><ul><ul><ul><li>The similarity between MCP semantic descriptions and the user questions is calculated. </li></ul></ul></ul><ul><ul><ul><ul><li>Cosine Similarity </li></ul></ul></ul></ul>MCP Ontology – Efficient Search C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    12. 12. MCP Ontology - Managing a certain medical case <ul><ul><li>Dynamic semantic composition of a sequence of algorithms </li></ul></ul><ul><ul><ul><li>Using semantic rules, the links between different algorithms are created and used in the construction of a Finite State Machine ( FSM ) of algorithms . </li></ul></ul></ul><ul><ul><ul><ul><li>1 st Set of Rules: Define the Possible Prerequisites Algorithms of an algorithmic solution. (Input/Output Variables) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>2 nd Set of Rules: Define the Possible Related Algorithms of an algorithmic solution. (Output/Output Variables) </li></ul></ul></ul></ul><ul><ul><ul><li>Description of a certain medical case via the MCP Ontology by a user constitutes the language of that case which is recognised by a FSM of algorithms with the final algorithm managing the case as the initial state and the algorithm of initiation by the user as the final state. </li></ul></ul></ul><ul><ul><ul><ul><li>Set of Rules: Define the Available Algorithmic Solutions for a specific medical case ( Pre-conditions are met) </li></ul></ul></ul></ul>
    13. 13. KnowBaSICS-M Modular Architecture
    14. 14. KnowBaSICS-M Technical Architecture Diagram <ul><li>Code development was based on open-source development platforms and tools : ( Protégé , Java, Jena, eclipse , Millstone ) </li></ul><ul><li>The system consists of: </li></ul><ul><ul><li>MCP Management Server </li></ul></ul><ul><ul><li>2 Clients </li></ul></ul><ul><ul><ul><li>Java Standalone </li></ul></ul></ul><ul><ul><ul><li>Web Client </li></ul></ul></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    15. 15. Experimental evaluation - Goals <ul><li>To evaluate KnowBaSICS-M either for knowledge insertion or for knowledge retrieval in order to assess its usability. </li></ul><ul><li>To calculate the precision and recall features. </li></ul><ul><li>To evaluate KnowBaSICS-M to manage specific cases by dynamically semantic composite algorithmic sequences </li></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    16. 16. Evaluation Process C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    17. 17. Experimental Results Similarity Similarity C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras New MCPs Satisfy Answer
    18. 18. Experimental Results of Search Precision Recall harmonic mean C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    19. 19. Test Case 1. Search similar MCP: Treatment of massive pulmonary embolism2. Find Algorithmic Sequence to manage a specific case C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras
    20. 20. Future Research <ul><li>Major technical challenge is the automated incorporation of the content located at existing repositories such as MedAl in the MCP KB (wrapper-mediation based) </li></ul><ul><li>An extension of KnowBaSICS-M is considered to support the automated identification of individualised algorithms that will be linked with Electronic Health Record (EHR) data (Archetype - OpenEHR ) , </li></ul><ul><li>High quality medical education ( Problem Based Learning & Case Based Learning - HealthCare LOM -SCORM) </li></ul><ul><li>Semantic Wiki about algorithmic medicine </li></ul><ul><ul><li>combination of web-2.0 and Semantic Web (e.g. wiki professional) </li></ul></ul>C Bratsas, P Bamidis *, E Kaimakamis, N Maglaveras

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