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As computerized health-care support systems are rapidly becoming more knowledge intensive, the representation of medical knowledge in a form that enables reasoning is growing in relevance and taking a more central role in the area of Medical Informatics. In order to achieve a successful decision-support and knowledge management approach to medical knowledge representation, the scientific community has to provide efficient representations, technologies, and tools to integrate all the important elements that health care providers work with: electronic health records and healthcare information systems, clinical practice guidelines and standardized medical technologies,
codification standards, etc.

Synergies to integrate the above mentioned elements and types of knowledge must be sought both in the medical problems (e.g., prevention, diagnosis, therapy, prognosis, etc.) and also in the Computer Science and Artificial Intelligence technologies (e.g., natural language processing, digital libraries, knowledge representation, knowledge integration and merging, decision support systems, machine learning, e-learning, etc.).

The third international KR4HC workshop will aim at attracting the interest of novel research and advances contributing in the definition, representation and exploitation of health care knowledge in medical informatics. Both well-founded theoretical works and applications are welcome.

Scope

Original contributions are sought, regarding the development of theory, techniques, and use cases of Artificial Intelligence in the area of health care, particularly connected to patient data, guidelines and medical processes. The scope of the workshop includes, but is not limited to, the following areas:

Binding formal knowledge and electronic patient records

o The use of ontologies, conceptual models and medical vocabularies for linking computerized guidelines and protocols to EPRs
o Techniques for simulating computerized guidelines against the content of EPRs
o Evaluation of quality and safety of computerized guidelines in the light of EPR data
o Checking compliance with guidelines and protocols against EPRs, including the use of quality indicators
o Interoperability of clinical guidelines for EPRs with comorbidity
o Use cases and deployments of computerized guidelines and protocols with EPRs

Health care knowledge development, management, validation and operation

o Knowledge representation and ontologies for health-care processes
o Formalization of medical processes and knowledge-based health-care models
o The use of ontologies, conceptual models and medical vocabularies for representing descriptive and procedural medical knowledge
o Combining medical guidelines with care pathways and the care delivery process
o Knowledge extraction from health-care databases and EPRs
o Temporal knowledge representations and exploitation
o Knowledge combination, personalization and adaptation for health care processes
o Knowledge validation (e.g., checking compliance with guidelines and protocols against patient data, the use of quality indicators, or simulation of guideline against patient data)
o Digital libraries and repositories of health-care procedural knowledge, guidelines and protocols
o Knowledge-based learning of health-care processes (e.g., data mining form guideline construction)
o Use case and deployments of formal representation of descriptive and procedural medical knowledge
o Patient empowerment trend in health care (e.g., preventive medicine requires patient empowerment for it to be effective)
o Linking clinical care and clinical research
o Use of biomedical data for medical care (e.g., biomarkers are able to predict a patient's response to a specific drug or treatment)

Tools, systems and applications

o Methods and tools for change and version management of descriptive and procedural medical knowledge
o Acquisition, refinement and exploration of the temporal aspect of guidelines and protocols
o Supporting the life cycle of guidelines and protocols
o Experiences in deploying knowledge-based tools in health care
o Applications and results of knowledge models in real medical settings