ORCID as entered in ROS

Select Publications
2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in South Australia, 2013-2022, UNSW Sydney, Sydney, 350, http://dx.doi.org/10.26190/y21d-yd24, https://ndarc.med.unsw.edu.au/resource/sa-trends-use-opioid-agonist-treatment-australia-2013-2022
,2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in Tasmania, 2013-2022, UNSW Sydney; National Drug and Alcohol Research Centre, Sydney, 351, http://dx.doi.org/10.26190/q6zj-fx75, https://ndarc.med.unsw.edu.au/resource/tas-trends-use-opioid-agonist-treatment-australia-2013-2022
,2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in the Australian Capital Territory, 2013-2022, UNSW Sydney; NDARC, Sydney, 346, http://dx.doi.org/10.26190/16m9-6z16, https://ndarc.med.unsw.edu.au/resource/ndarc-technical-reports-345-353
,2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in the Northern Territory, 2013-2022, UNSW Sydney, Sydney, 348, http://dx.doi.org/10.26190/mt8r-kd57, https://ndarc.med.unsw.edu.au/resource/nt-trends-use-opioid-agonist-treatment-australia-2013-2022
,2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in Victoria, 2013-2022, UNSW Sydney; National Drug and Alcohol Research Centre, Sydney, 352, http://dx.doi.org/10.26190/gjpp-py45, https://ndarc.med.unsw.edu.au/resource/vic-trends-use-opioid-agonist-treatment-australia-2013-2022
,2023, NDARC Technical Report: Trends in the use of Opioid Agonist Treatment in Western Australia, 2013-2022, UNSW Sydney; National Drug and Alcohol Research Centre, Sydney, 353, http://dx.doi.org/10.26190/ftbz-w461, https://ndarc.med.unsw.edu.au/resource/wa-trends-use-opioid-agonist-treatment-australia-2013-2022
,2022, Towards measuring effective coverage: critical bottlenecks in quality- and user-adjusted coverage for major depressive disorder in São Paulo metropolitan area, Brazil., http://dx.doi.org/10.21203/rs.3.rs-1534962/v1
,2020, Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach, http://dx.doi.org/10.48550/arxiv.2011.14032
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