The Biomedical Data Science Laboratory uses knowledge as the infrastructure to support decision making in biomedicine, most notably by assisting clinicians and biologists in cancer diagnosis and treatment.
Biomedical Data Science Lab
Professor Paul Kennedy | Lab Director
Professor Daniel Catchpoole | Lab Co-Director
The Biomedical Data Science Lab's mission is to examine and build data pipelines for the new age of data in the form of software tools that can examine, extract and transport knowledge throughout these ecologies. Research focuses on improving knowledge discovery and decision-making in large, distributed open systems.
Data analytics in biomedical and clinical domains
The Biomedical Data Science (BDS) Lab aims to develop computational intelligence for decision making in biomedical and clinical domains. The lab’s research team is helping to predict treatment outcomes for paediatric cancer and is assisting in vaccine discovery methods for agriculture. Researchers at Biomedical Data Science Lab are also developing approaches for text analytics in social media and language design, and knowledge discovery using pattern calculus.
Left: Predicting treatment outcomes for childhood cancers with the Children's Hospital at Westmead. Using a virtual reality platform, clinicians compare the human genome and treatment outcomes of people affected by cancer to provide personalised treatment plans. Image: Silver Orchid / Pixabay
Centre: The bondi language implements pattern matching using pattern calculus.
Right: Data from thousands of tumour specimens is used by the Lab's software to compare gene expressions and biological variants in patients.
