CSIRO delves into genomics integration and data analytics at HealthData21

Data is the life blood of our healthcare system. Collected at the point of care it can be used to support patients as well as informing health statistics, funding purposes, improving service delivery and research. When new data come along – such as genomic DNA sequences – consideration for how to best to use that data to improve patient care, health outcomes and system performance is required.

The first day at the HealthData21 conference will focus on how we use genomic data to improve patient health while the focus of the second day will address data use across our health systems.

The Australian e-Health Research Centre, CSIRO’s digital health research program, works with data across the system – from genomic data for diagnosis and treatment, imaging and other biomedical data, data captured in electronic health records and clinical reports and data that is collected with sensors or through mobile devices.

At this year’s HealthData21, we’ll hear from Dr David Hansen, the CEO of the Australian e-Health Research Centre. David will use examples from CSIRO and experience from around the world to talk about what’s happening with the integration of genomics into healthcare.

Dr Sankalp Khanna is a Principal Research Scientist at CSIRO, he will deliver a masterclass entitled Analytics driven healthcare. Predicting patient flow has the potential to elevate healthcare by improving efficiencies across the system. Sankalp will use examples of his work to show how facilities can benefit from this model.

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If you stopped and had a chat with the team from CSIRO’s Australian e-Health Research Centre at the HealthData21 Conference, thanks for stopping by! Read on for case studies and other bits and bobs to give you more info about us and the kind of work we do.

If you couldn’t make it, no problems – you can still hear about our latest work right here.

AEHRC 2019-2020 Annual Report

For more than 15 years we have been delivering scalable, innovative solutions and research to solve some of the greatest health and healthcare challenges throughout Australia and the world. Despite the COVID-19 disruption, our 100+ staff and students have been working flat-out over the past year. Read all the details in our 2019-2020 Annual Report.

A screenshot of a report cover. The heading says "The Australian e-Health Research Centre Annual Report 2019-2020". There is an image of a man in safety goggles and a medical mask looking at a screen, along with images of brain scans.

Read our 2019-2020 annual report.

Applying artificial intelligence and machine learning to healthcare

From genomic engineering to independent living, the Australian e-Health Research Centre is using artificial intelligence techniques and machine learning approaches to overcome the challenges facing the healthcare system and improve health service delivery to Australians. 

Our new report shows how our AI techniques are powering digital health: from understanding whole genome sequences to enabling clinical decision support, determining patient risk prediction, understanding older people’s functional wellbeing and more.

Read the full report: Exemplars of Artificial Intelligence and Machine Learning in Healthcare (PDF).

A screenshot of a report cover. A colourful brain scan image fills the top half; the heading says "Exemplars of Artificial Intelligence and Machine Learning in Healthcare"

Our 2020 report details the use of AI in healthcare.

Case studies that demonstrate real-world digital health transformation

Below are some examples of the work we’ve done in collaboration with key partners to address Australia’s digital healthcare challenges.

Mobile support for total knee replacement

Cloud-based tools for Cerebral Palsy neuroimaging

Biomarkers for diabetic retinopathy

Clinical Terminology and FHIR

GTScan Suite – computationally guiding genome engineering

Retinal imaging markers of accumulated blood pressure burden

Medtex – unlocking the value of medical narratives

Mobile platform for gestational diabetes support

FHIR Analytics Server Pathling

Improving data quality using FHIR and SNOMED-CT

AI-powered MRI tool to improve prostate cancer treatment

Serverless Beacon – making genomic data-sharing future-ready

sVEP – accelerating variant annotation and curation

CHSP Smarter Safer Homes Project

Smarter Safer Homes Dementia and Aged Care Services project

Socially-assistve robots in therapy and education

Deep learning segmentation in Stargardt disease

Teledentistry to improve dental health in school children

TRIBES – relatedness detection in genomic data

VariantSpark: machine learning for ultra-high dimensional data

Want to find out more? We’d love to hear from you! Contact us at enquiries@aehrc.com.