Overview
Background
Dr. Sebastiano Barbieri is Associate Professor and Principal Research Fellow at the Queensland Digital Health Centre, University of Queensland (UQ) and Adjunct Associate Professor at the Centre for Big Data Research in Health, University of New South Wales (UNSW). His work lies at the intersection of machine learning and healthcare, where he develops innovative computational methods to tackle pressing challenges in medicine.
Aiming to improve patient outcomes and streamline clinical workflows, Dr. Barbieri develops machine learning models tailored to real-world healthcare applications. His current research spans risk prediction using electronic medical records, medical image processing, and the safe and effective integration of AI into clinical decision-making processes.
A strong advocate for responsible AI in healthcare, Dr. Barbieri champions the use of emerging technologies such as synthetic data generation and federated learning. These approaches not only enhance data accessibility and privacy but also accelerate the development of robust, data-driven solutions for digital health.
Availability
- Associate Professor Sebastiano Barbieri is:
- Available for supervision
Qualifications
- Bachelor of Mathematics, Universität des Saarlandes
- Masters (Coursework) of Image Processing, Universität des Saarlandes
- Doctor of Philosophy of Computer Science, Jacobs University
- Masters (Coursework) of Biostatistics, Macquarie University
Works
Search Professor Sebastiano Barbieri’s works on UQ eSpace
2023
Journal Article
Sexual and drug use risk behaviour trajectories among people treated for recent HCV infection: the REACT study
Carson, Joanne M., Barbieri, Sebastiano, Cunningham, Evan, Mao, Eric, van der Valk, Marc, Rockstroh, Jürgen K., Hellard, Margaret, Kim, Arthur, Bhagani, Sanjay, Feld, Jordan J., Gane, Ed, Thurnheer, Maria C., Bruneau, Julie, Tu, Elise, Dore, Gregory J., Matthews, Gail V. and Martinello, Marianne (2023). Sexual and drug use risk behaviour trajectories among people treated for recent HCV infection: the REACT study. Journal of the International AIDS Society, 26 (9) e26168. doi: 10.1002/jia2.26168
2023
Journal Article
Generating synthetic clinical data that capture class imbalanced distributions with generative adversarial networks: example using antiretroviral therapy for HIV
Kuo, Nicholas I-Hsien, Garcia, Federico, Sönnerborg, Anders, Böhm, Michael, Kaiser, Rolf, Zazzi, Maurizio, Polizzotto, Mark, Jorm, Louisa and Barbieri, Sebastiano (2023). Generating synthetic clinical data that capture class imbalanced distributions with generative adversarial networks: example using antiretroviral therapy for HIV. Journal of Biomedical Informatics, 144 104436, 104436. doi: 10.1016/j.jbi.2023.104436
2023
Journal Article
Increasing national trend of direct-acting antiviral discontinuation among people treated for HCV 2016-2021
Carson, Joanne, Barbieri, Sebastiano, Matthews, Gail V., Dore, Gregory J. and Hajarizadeh, Behzad (2023). Increasing national trend of direct-acting antiviral discontinuation among people treated for HCV 2016-2021. Hepatology Communications, 7 (4) e0125. doi: 10.1097/HC9.0000000000000125
2022
Journal Article
Incorporating uncertainty in learning to defer algorithms for safe computer-aided diagnosis
Liu, Jessie, Gallego, Blanca and Barbieri, Sebastiano (2022). Incorporating uncertainty in learning to defer algorithms for safe computer-aided diagnosis. Scientific Reports, 12 (1) 1762, 1-9. doi: 10.1038/s41598-022-05725-7
2022
Journal Article
The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms
Kuo, Nicholas I-Hsien, Polizzotto, Mark N., Finfer, Simon, Garcia, Federico, Sonnerborg, Anders, Zazzi, Maurizio, Boehm, Michael, Kaiser, Rolf, Jorm, Louisa and Barbieri, Sebastiano (2022). The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms. Scientific Data, 9 (1) 693, 1-24. doi: 10.1038/s41597-022-01784-7
2022
Journal Article
Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer
Ottens, Tim, Barbieri, Sebastiano, Orton, Matthew R., Klaassen, Remy, van Laarhoven, Hanneke W.M., Crezee, Hans, Nederveen, Aart J., Zhen, Xiantong and Gurney-Champion, Oliver J. (2022). Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer. Medical Image Analysis, 80 102512, 1-12. doi: 10.1016/j.media.2022.102512
2022
Journal Article
Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach
Barbieri, Sebastiano, Mehta, Suneela, Wu, Billy, Bharat, Chrianna, Poppe, Katrina, Jorm, Louisa and Jackson, Rod (2022). Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach. International Journal of Epidemiology, 51 (3), 931-944. doi: 10.1093/ije/dyab258
2022
Journal Article
A machine learning approach to predict the added-sugar content of packaged foods
Davies, Tazman, Louie, Jimmy Chun Yu, Ndanuko, Rhoda, Barbieri, Sebastiano, Perez-Concha, Oscar and Wu, Jason H. Y (2022). A machine learning approach to predict the added-sugar content of packaged foods. Journal of Nutrition, 152 (1), 343-349. doi: 10.1093/jn/nxab341
2021
Journal Article
Using administrative data to predict cessation risk and identify novel predictors among new entrants to opioid agonist treatment
Bharat, Chrianna, Degenhardt, Louisa, Dobbins, Timothy, Larney, Sarah, Farrell, Michael and Barbieri, Sebastiano (2021). Using administrative data to predict cessation risk and identify novel predictors among new entrants to opioid agonist treatment. Drug and Alcohol Dependence, 228 109091, 1-8. doi: 10.1016/j.drugalcdep.2021.109091
2021
Journal Article
Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients
Kaandorp, Misha P. T., Barbieri, Sebastiano, Klaassen, Remy, van Laarhoven, Hanneke W. M., Crezee, Hans, While, Peter T., Nederveen, Aart J. and Gurney-Champion, Oliver J. (2021). Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients. Magnetic Resonance in Medicine, 86 (4), 2250-2265. doi: 10.1002/mrm.28852
2021
Journal Article
Psychotropic medicine prescribing and polypharmacy for people with dementia entering residential aged care: the influence of changing general practitioners
Welberry, Heidi J., Jorm, Louisa R., Schaffer, Andrea L., Barbieri, Sebastiano, Hsu, Benjumin, Harris, Mark F., Hall, John and Brodaty, Henry (2021). Psychotropic medicine prescribing and polypharmacy for people with dementia entering residential aged care: the influence of changing general practitioners. Medical Journal of Australia, 215 (3), 130-136. doi: 10.5694/mja2.51153
2021
Journal Article
Big data and predictive modelling for the opioid crisis: existing research and future potential
Bharat, Chrianna, Hickman, Matthew, Barbieri, Sebastiano and Degenhardt, Louisa (2021). Big data and predictive modelling for the opioid crisis: existing research and future potential. The Lancet Digital Health, 3 (6), e397-e407. doi: 10.1016/S2589-7500(21)00058-3
2021
Journal Article
The effect of person, treatment and prescriber characteristics on retention in opioid agonist treatment: a 15-year retrospective cohort study
Bharat, Chrianna, Larney, Sarah, Barbieri, Sebastiano, Dobbins, Timothy, Jones, Nicola R., Hickman, Matthew, Gisev, Natasa, Ali, Robert and Degenhardt, Louisa (2021). The effect of person, treatment and prescriber characteristics on retention in opioid agonist treatment: a 15-year retrospective cohort study. Addiction, 116 (11), 3139-3152. doi: 10.1111/add.15514
2020
Journal Article
Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative data
Welberry, Heidi J., Brodaty, Henry, Hsu, Benjumin, Barbieri, Sebastiano and Jorm, Louisa R. (2020). Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative data. Scientific Reports, 10 (1) 8781, 1-14. doi: 10.1038/s41598-020-65273-w
2020
Journal Article
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk
Barbieri, Sebastiano, Kemp, James, Perez-Concha, Oscar, Kotwal, Sradha, Gallagher, Martin, Ritchie, Angus and Jorm, Louisa (2020). Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk. Scientific Reports, 10 (1) 1111, 1-10. doi: 10.1038/s41598-020-58053-z
2020
Journal Article
Impact of Prior Home Care on Length of Stay in Residential Care for Australians With Dementia
Welberry, Heidi J., Brodaty, Henry, Hsu, Benjumin, Barbieri, Sebastiano and Jorm, Louisa R. (2020). Impact of Prior Home Care on Length of Stay in Residential Care for Australians With Dementia. Journal of the American Medical Directors Association, 21 (6), 843-850.e5. doi: 10.1016/j.jamda.2019.11.023
2020
Journal Article
Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI
Barbieri, Sebastiano, Gurney-Champion, Oliver J., Klaassen, Remy and Thoeny, Harriet C. (2020). Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI. Magnetic Resonance in Medicine, 83 (1), 312-321. doi: 10.1002/mrm.27910
2018
Journal Article
Enhancing patient value efficiently: Medical history interviews create patient satisfaction and contribute to an improved quality of radiologic examinations
Nairz, Knud, Böhm, Ingrid, Barbieri, Sebastiano, Fiechter, Dieter, Hošek, Nicola and Heverhagen, Johannes (2018). Enhancing patient value efficiently: Medical history interviews create patient satisfaction and contribute to an improved quality of radiologic examinations. PLoS One, 13 (9) e0203807, 1-16. doi: 10.1371/journal.pone.0203807
2018
Journal Article
Comparison of six fit algorithms for the intravoxel incoherent motion model of diffusionweighted magnetic resonance imaging data of pancreatic cancer patients
Gurney-Champion, Oliver J., Klaassen, Remy, Froeling, Martijn, Barbieri, Sebastiano, Stoker, Jaap, Engelbrecht, Marc R. W., Wilmink, Johanna W., Besselink, Marc G., Bel, Arjan, Van Laarhoven, Hanneke W.M. and Nederveen, Aart J. (2018). Comparison of six fit algorithms for the intravoxel incoherent motion model of diffusionweighted magnetic resonance imaging data of pancreatic cancer patients. PLoS One, 13 (4) e0194590, 1-18. doi: 10.1371/journal.pone.0194590
2017
Journal Article
Selection for biopsy of kidney transplant patients by diffusion-weighted MRI
Steiger, Philipp, Barbieri, Sebastiano, Kruse, Anja, Ith, Michael and Thoeny, Harriet C. (2017). Selection for biopsy of kidney transplant patients by diffusion-weighted MRI. European Radiology, 27 (10), 4336-4344. doi: 10.1007/s00330-017-4814-z
Supervision
Availability
- Associate Professor Sebastiano Barbieri is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Available projects
-
Machine learning for the generation and distribution of synthetic electronic medical records (EMRs) representative of the Australian population
This project will develop a novel software and data platform, comprising nationally representative synthetic EMR data, to enable safe and ethical Australian innovation in clinical artificial intelligence.
Supervision history
Current supervision
-
Doctor Philosophy
NINA national infrastructure for digital health
Principal Advisor
Other advisors: Professor Clair Sullivan
-
Master Philosophy
Investigating the Impact of Artificial Intelligence on Clinical Workflows, Efficiency, and Health Economics: Implementation Insights, Bias Evaluation, and Strategic Mitigation strategies for Clinical AI Integration
Principal Advisor
Other advisors: Professor Ian Scott, Dr Anton van Der Vegt
-
Doctor Philosophy
Machine learning for generation and distribution of synthetic electronic medical records (EMRs) representative of the Australian population
Principal Advisor
Other advisors: Dr Guanglin Zhou
Media
Enquiries
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