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2022 Journal Article Incorporating uncertainty in learning to defer algorithms for safe computer-aided diagnosisLiu, 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 |
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2022 Journal Article The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithmsKuo, 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 |
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2022 Journal Article Deep learning DCE-MRI parameter estimation: Application in pancreatic cancerOttens, 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 |
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2022 Journal Article Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approachBarbieri, 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 |
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2022 Journal Article A machine learning approach to predict the added-sugar content of packaged foodsDavies, 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 |
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2021 Journal Article Using administrative data to predict cessation risk and identify novel predictors among new entrants to opioid agonist treatmentBharat, 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 |
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2021 Journal Article Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patientsKaandorp, 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 |
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2021 Journal Article Psychotropic medicine prescribing and polypharmacy for people with dementia entering residential aged care: the influence of changing general practitionersWelberry, 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 |
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2021 Journal Article Big data and predictive modelling for the opioid crisis: existing research and future potentialBharat, 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 |
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2021 Journal Article The effect of person, treatment and prescriber characteristics on retention in opioid agonist treatment: a 15-year retrospective cohort studyBharat, 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 |
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2020 Journal Article Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative dataWelberry, 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 |
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2020 Journal Article Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-RiskBarbieri, 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 |
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2020 Journal Article Impact of Prior Home Care on Length of Stay in Residential Care for Australians With DementiaWelberry, 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 |
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2020 Journal Article Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRIBarbieri, 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 |
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2018 Journal Article Enhancing patient value efficiently: Medical history interviews create patient satisfaction and contribute to an improved quality of radiologic examinationsNairz, 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 |
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2018 Journal Article Comparison of six fit algorithms for the intravoxel incoherent motion model of diffusionweighted magnetic resonance imaging data of pancreatic cancer patientsGurney-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 |
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2017 Journal Article Selection for biopsy of kidney transplant patients by diffusion-weighted MRISteiger, 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 |
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2017 Journal Article Differentiation of prostate cancer lesions with high and with low Gleason score by diffusion-weighted MRIBarbieri, Sebastiano, Brönnimann, Michael, Boxler, Silvan, Vermathen, Peter and Thoeny, Harriet C. (2017). Differentiation of prostate cancer lesions with high and with low Gleason score by diffusion-weighted MRI. European Radiology, 27 (4), 1547-1555. doi: 10.1007/s00330-016-4449-5 |
