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Artificial intelligence (AI) and machine learning techniques are being harnessed to power digital health: from understanding whole genome sequences to enabling clinical decision support, determining patient risk prediction, understanding older people’s functional wellbeing and more.
Established more than 15 years ago, CSIRO’s world-leading Australian e-Health Research Centre (AEHRC) has been at the forefront of using AI to enable Australia’s digital health future. Its 100+ scientists and engineers collaborate closely with government and industry to tackle the key challenges of 21st century healthcare.
From genomic engineering to independent living, the AEHRC is using artificial intelligence techniques and machine learning approaches to overcome the challenges facing the healthcare system and improve health service delivery to Australians, including:
- Improving prostate radiation therapy: developing AI-based software to support prostate cancer radiation treatment planning.
- Reasoning on medical knowledge: using AI to develop a snorocket Description Logic classifier that can be used on ontologies such as SNOMED CT to ‘reason’ about medical knowledge.
- Supporting ageing in place: using AI to develop a low-cost, non-invasive sensor, monitoring and support system to support older people living in individual homes or supported-living communities.
- Making genomic research faster: developing VariantSpark, a new random forest algorithm, whose speed and higher sensitivity opens up the use of advanced, efficient machine learning algorithms on high dimensional genomic data.
- Understanding virus evolution: using machine learning-based technology to make sense of a pathogen’s evolutionary drift, by visualising the genomic fingerprint unique to virus isolates sequenced around the world. In 2020 this was used to analyse the virus that causes COVID-19.
Read about these case studies and more in the AEHRC’s new report, Exemplars of Artificial Intelligence and Machine Learning in Healthcare.