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Health Data Management & Semantics

Data is captured about patients in a number of different formats, electronic repositories and using many different terminologies. Our technologies are targeted at understanding the information in data, whether the data is captured in an electronic health record, coded in a clinical database, physiological data captured from sensors, described in free text in pathology reports or even captured using imaging technology. Our tools for using and building clinical terminologies can be used to describe data in a way which is machine readable. New statistical algorithms and visualisation techniques that form part of our research and development provide analysis and display of the data for clinicians, researchers and patients.

Clinical Data Acquisition, Integration, Visualisation & Analysis supporting research into neurodegenerative diseases such as Alzheimer's disease and Stroke for the Preventative Health National Flagship.
Clinical Terminology Tools developing tools to collect health information in a standard way.
  • Minnow, a SNOMED CT browser.
  • Snorocket, a fast classifier for ontologies, such as SNOMED CT.
  • Snapper Platform, a tool for mapping one terminolgies to concepts or expressions of another terminology.
  • Ontoserver, a terminology server
Combo-Test generating test suites with a minimal set of test cases controllable by the System Under Test inputs and a pre-configured strength control.
Medical Free Text Processing extracting clinical information from free text reports.
Mining Large Complex Datasets developing database and data mining techniques to retrieve rich information from large and complex data sets.

Last Updated on Wednesday, 05 October 2011 07:37

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Dr Michael Lawley

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