Auckland Bioengineering Institute


Biomedical Informatics

Biomedical Informatics

Biomedical informatics is the science of information as applied to or studied in the context of biomedicine. As an informatics area it is primarily concerned with data plus meaning (aka semantics) and provides methods to tackle concepts that are hard to capture using formal, computational definitions.

While it is used synonymously with health informatics by many, we distinguish our group’s interests by being more focussed on hard aspects such as formal information and knowledge methods and standards, semantic web, digital patient, decision support, interoperability as well as software and development work.

The aim of our group is to link clinical information and workflows to computational models and tools, in order to bring about personalised, predictive and quantitative approaches to Biomedicine, and help realise the Physiome Project / Virtual Physiological Human initiatives. This, we believe, will pave the way to new breakthroughs and coming of next generation clinical decision support tools and new technologies.
 

Members and collaborators


Members

Group leader

Portrait of

Koray Atalag
Senior Research Fellow
Email: k.atalag@auckland.ac.nz

Reza Kalbasi

Reza Kalbasi
Doctoral Candidate
Email: r.kalbasi@auckland.ac.nz

Portrait of

David Nickerson
Senior Research Fellow
Email: d.nickerson@auckland.ac.nz

Associates and collaborators

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Current projects


MedTech CoRE – Platform 5: Software and Modelling

The aim of the project is to represent measurement data and associated clinical information using openEHR archetypes and then map to CellML and FieldML parameters for model validation, and to create next generation of personalised and predictive decision support tools at the bedside.

An openEHR compliant research data repository will be set up to store clinical and experimental which will allow for semantic annotation using biomedical ontologies (for example FMA, Human Phenotype Ontology etc.) and clinical terminology (for example SNOMED CT, LOINC etc.).
 

Annotation of clinical datasets using openEHR Archetypes (PhD research – Aleksandar Zivaljevic)

Linking of computational models and clinical data requires agreement on common semantics, which should be understood by computers without human intervention. This project aims to use the openEHR electronic health record (EHR) standard as the semantic glue to make this connection.

Health information models, called Archetypes, will be annotated using shared ontologies. They will be utilised by the Physiome Model Repository (PMR) as meta-data, to link to associated computational models. The aim is to create an advanced semantic search functionality that can drive the development of model and data driven clinical decision tools and new knowledge discovery. For more information, see the paper Annotation of clinical datasets using openEHR Archetypes as a solution for data access issues faced in biomedical projects.

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Selected publications


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Postgraduate opportunities


We seek excellent and motivated doctoral and masters students to work with who preferably have existing relevant experience and technical skills.

If you have a graduate project you would like to propose or would like further information on current projects, please contact:

Portrait of

Koray Atalag
Senior Research Fellow
Email: k.atalag@auckland.ac.nz

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