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Sebastiano Barbieri
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Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models


Mar 22, 2023
Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

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Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV


Aug 18, 2022
Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri

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* In the near future, we will make our codes and synthetic datasets publicly available to facilitate future research. Follow us on https://healthgym.ai/ 
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The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms


Mar 12, 2022
Nicholas I-Hsien Kuo, Mark N. Polizzotto, Simon Finfer, Federico Garcia, Anders Sönnerborg, Maurizio Zazzi, Michael Böhm, Louisa Jorm, Sebastiano Barbieri

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Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project


Dec 07, 2021
Nicholas I-Hsien Kuo, Mark Polizzotto, Simon Finfer, Louisa Jorm, Sebastiano Barbieri

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Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis


Sep 03, 2021
Jessie Liu, Blanca Gallego, Sebastiano Barbieri

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Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach


Nov 28, 2020
Sebastiano Barbieri, Suneela Mehta, Billy Wu, Chrianna Bharat, Katrina Poppe, Louisa Jorm, Rod Jackson

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Improved unsupervised physics-informed deep learning for intravoxel-incoherent motion modeling and evaluation in pancreatic cancer patients


Nov 03, 2020
Misha P. T. Kaandorp, Sebastiano Barbieri, Remy Klaassen, Hanneke W. M. van Laarhoven, Hans Crezee, Peter T. While, Aart J. Nederveen, Oliver J. Gurney-Champion

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A Deep Representation of Longitudinal EMR Data Used for Predicting Readmission to the ICU and Describing Patients-at-Risk


May 21, 2019
Sebastiano Barbieri, Oscar Perez-Concha, Sradha Kotwal, Martin Gallagher, Angus Ritchie, Louisa Jorm

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