KDRC aims to ensure the scalability of data and information governance, whilst promoting effective collaboration and communication between researchers, academia and industry. By unifying data and technology the centre hopes to streamline the pace of progress in health data analytics and research.

Our work on health sciences has been divided into follow categories.

  1. Medical Decision Support Systems
  2. Medical Ontologies
  3. HL7 Standards

HL7 Standards

HL7 and its members provide a framework (and related standards) for the exchange, integration, sharing, and retrieval of electronic health information. These standards define how information is packaged and communicated from one party to another, setting the language, structure and data types required for seamless integration between systems. HL7 standards are recognized as the most commonly used in the world.

Medical Ontologies

Research in ontology is increasingly gaining importance for knowledge modeling, the semantic foundation of knowledge representation and for the development of meta-models in the area of practical applications. In this connection problems regarding the applications in the field of medicine are of particular interest.

Medical Decision Support Systems

Medical Decision Support Systems (MDSS) play an increasingly important role in medical practice. By assisting doctors with making clinical decisions, DSS are expected to improve the quality of medical care.  Data mining may be conducted to examine the patient’s medical history in conjunction with relevant clinical research. Such analysis can help predict potential events, which can range from drug interactions to disease symptoms.