Enhancing the health and wellbeing of all through the productive use of big data.
At the Centre for Big Data Research in Health (CBDRH) we aim to enhance the health and wellbeing of all, by maximising the productive use of all possible sources of health big data in medical research.
We are Australia’s first research centre dedicated to health research using big data. Our research is collaborative, involving codesign and coproduction methods with consumers, communities and health care providers. Together, we aim to facilitate long term translation and implementation into health policy, service and programs.
We are privileged to have many enthusiastic partners including government agencies, health organisations from the public, private and not-for-profit sectors, research funders, clinicians, health consumers and community members.
We are Australia’s first research centre dedicated to health research using large-scale electronic data spanning the biomedical, clinical, health services and public health domains.
At the CBDRH, we integrate health data science into everything we do. Our science is an evolving discipline that responds to the growing number of large and complex datasets in health and medicine.
Research at the CBDRH tackles a broad range of health issues using large-scale electronic data.
The NPESU is also data custodian of the Australian and New Zealand Assisted Reproduction Database (ANZARD), the Australian and New Zealand Neonatal Network (ANZNN), the International Committee for Monitoring Assisted Reproductive Technologies (ICMART) World IVF Registry, and the YourIVFSuccess website.
The CardiacAI clinical registry supports rapid translational cardiac research and advanced AI-based decision support tool development and validation. It uses data drawn directly from Cerner electronic medical record (EMR) systems in four major hospitals in urban and regional NSW.
‘Health Gym’ is an open platform providing synthetic health-related data to the machine learning and clinical research communities. The primary purpose of these data is to allow researchers to easily prototype, test and compare offline reinforcement learning (RL) algorithms.
ERICA is secure cloud computing infrastructure for individuals working with sensitive, often large-scale data. It provides a highly secure, yet highly functional, computing environment that enables cutting-edge data analytics and reporting.
The Machine Learning in Health Club is a semi-formal weekly seminar hosted by the Centre for Big Data Research in Health.
We work with a number of Clinical Quality Registries including: