Arrow Left Health care

Use case: OzCAT: The Australian Computer Aided Theragnostics network

Many patients do not meet randomised clinical trial criteria on which radiotherapy treatment guidelines are based. An Australian distributed radiotherapy data network has been established including international partners. The aim of this data-network is to enable the generation of additional clinical evidence to support treatment decisions for patients by machine learning of prediction models. Next to this, it aims to yield more effective clinical trials, detecting cancer practice variations. Furthermore, the data-network drives improvement of data collection and accuracy in Australia to improve outcome prediction models.

Medical relevance

Improvement of shared decision making and decision support


ozCAT started in 2013 and is one of the first projects developing distributed learning concept which led to the Personal Health Train (PHT). It has established a distributed learning network in New South Wales and is extending to other states and territories. The ozCAT consortium will join the Personal Health Train community to make sure the ozCAT and PHT solutions for distributed learning are interoperable. The ozCAT PHT implementation has been applied in lung cancer and head-and-neck cancer and is deployed in more than 4 hospitals.

Main results

Non-small cell lung and head-and-neck cancer decision support based on distributed learning over multi-center data.

Lessons learned

Outcome prediction models for lung and head-and-neck cancer have been learned and validated across different Australian hospitals.

Follow up

The ozCAT consortium is still working together and extending with centers in Victoria, Queensland and Western Australia.

Project details


Project leader

Lois Holloway, Matthew Field

Funders Ministry of Health, New South Wales
Collaboration partners Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia / University of Wollongong, Australia / Cancer Therapy Centre, Liverpool Hospital, Australia / Illawarra Health and Medical Research Institute, Wollongong, Australia / Sydney West Radiation Oncology Network, NSW Australia / Calvary Mater Hospital Newcastle, NSW Australia / MAASTRO Clinic NL / University of Sydney, Australia.


Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting.
Oncotarget. 2016; 7:37288-37296

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