Knowledge Representation for Health-Care. Data, Processes and Guidelines AIME 2009 Workshop KR4HC 2009, Verona, Italy, July 19, 2009, Revised Selected Papers / edited by David Riano, Annette ten Teije, Silvia Miksch, Mor Peleg.

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Riano, David (Editor), ten Teije, Annette (Editor), Miksch, Silvia (Editor), Peleg, Mor (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edition:1st ed. 2010.
Series:Lecture Notes in Artificial Intelligence ; 5943
Springer eBook Collection.
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Table of Contents:
  • From Patient Data to Medical Ontologies
  • Creating Topic Hierarchies for Large Medical Libraries
  • Bridging an Asbru Protocol to an Existing Electronic Patient Record
  • From Natural Language Descriptions in Clinical Guidelines to Relationships in an Ontology
  • A Hybrid Methodology for Consumer-Oriented Healthcare Knowledge Acquisition
  • Identifying Disease-Centric Subdomains in Very Large Medical Ontologies: A Case-Study on Breast Cancer Concepts in SNOMED CT. Or: Finding 2500 Out of 300.000
  • Sharable Appropriateness Criteria in GLIF3 Using Standards and the Knowledge-Data Ontology Mapper
  • Guideline Modeling and Tools
  • Analysis of the GLARE and GPROVE Approaches to Clinical Guidelines
  • Semantic Web-Based Modeling of Clinical Pathways Using the UML Activity Diagrams and OWL-S
  • Extracting Qualitative Knowledge from Medical Guidelines for Clinical Decision-Support Systems
  • Experiences in the Development of Electronic Care Plans for the Management of Comorbidities
  • Challenges in Delivering Decision Support Systems: The MATE Experience
  • Technical Solutions for Integrating Clinical Practice Guidelines with Electronic Patient Records
  • Advanced Topics
  • Towards a Possibility-Theoretic Approach to Uncertainty in Medical Data Interpretation for Text Generation
  • Argumentation about Treatment Efficacy
  • A Knowledge-Management Architecture to Integrate and to Share Medical and Clinical Data, Information, and Knowledge.