Mr Oisin Fitzgerald

Mr Oisin Fitzgerald

Data Administrator

PhD, UNSW Sydney (2023)

Master of Statistics, UNSW Sydney (2018)

Medicine & Health
Centre for Big Data Research in Health

Oisin is an early career researcher and Senior Data Scientist in the National Perinatal Epidemiology and Statistics Unit. He completed his PhD in health data science at the Centre for Big Data Research in Health (CBDRH) at UNSW Sydney in collaboration with eHealth NSW and the CSIRO in 2023. He has published research on topics including novel deep learning methods for forecasting of physiological time series, causal inference, risk prediction and the impact of hyperglycaemia in critically ill patients. He currently primarily works on research related to assisted reproductive technology, an area in which he has authored several public and government reports, contributed to the development of clinical registries, developed statistical methodologies and software for ART clinic quality control, and more recently worked on the development of the YourIVFSuccess website which won the Research Australia "Innovative Use of Data" award in 2023. As part of the YourIVFSuccess website he lead the development of the Estimator, a machine learning tool built using >500,000 ART cycles that informs users of their chance of a livebirth from ART, and he continues to lead research  investigating potential future improvements.

Phone
02 9385 9463
  • Book Chapters | 2021
    Donnolley N; Rudd L; Fitzgerald O; Davies-Tuck M, 2021, 'Working as a Health Data Scientist', in Butler-Henderson K; Day K; Gray K (ed.), The Health Information Workforce, Springer Nature, Switzerland, pp. 237 - 246, http://dx.doi.org/10.1007/978-3-030-81850-0_16
  • Journal articles | 2024
    Fitzgerald O; Dyer S; Zegers-Hochschild F; Keller E; Adamson GD; Chambers GM, 2024, 'Gender inequalityãnd utilization of ART:ãn international cross-sectionalãnd longitudinalãnalysis', Human Reproduction, 39, pp. 209 - 218, http://dx.doi.org/10.1093/humrep/dead225
    Journal articles | 2023
    Brew BK; Donnolley N; Fitzgerald O; Molloy D; Chambers GM, 2023, 'Does a public online IVF prediction tool help set patient expectations? A mixed methods evaluation study', Human Reproduction, 38, pp. 1761 - 1768, http://dx.doi.org/10.1093/humrep/dead139
    Journal articles | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Metke-Jimenez A; Rudd L; Jorm L, 2023, 'Continuous time recurrent neural networks: Overview and benchmarking at forecasting blood glucose in the intensive care unit', Journal of Biomedical Informatics, 146, http://dx.doi.org/10.1016/j.jbi.2023.104498
    Journal articles | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 2023, 'The relationship between hyperglycaemia on admission and patient outcome is modified by hyperlactatemia and diabetic status: a retrospective analysis of the eICU collaborative research database', Scientific Reports, 13, http://dx.doi.org/10.1038/s41598-023-43044-7
    Journal articles | 2022
    Hanly M; Churches T; Fitzgerald O; Caterson I; MacIntyre CR; Jorm L, 2022, 'Modelling vaccination capacity at mass vaccination hubs and general practice clinics: a simulation study', BMC Health Services Research, 22, http://dx.doi.org/10.1186/s12913-022-08447-8
    Journal articles | 2022
    Hanly M; Churches T; Fitzgerald O; MacIntyre CR; Jorm L, 2022, 'Vaccinating Australia: How long will it take?', Vaccine, 40, pp. 2491 - 2497, http://dx.doi.org/10.1016/j.vaccine.2021.07.006
    Journal articles | 2022
    Hanly MJ; Churches T; Fitzgerald O; Post JJ; MacIntyre CR; Jorm L, 2022, 'The impact of re-opening the international border on COVID-19 hospitalisations in Australia: a modelling study', Medical Journal of Australia, 216, pp. 39 - 42, http://dx.doi.org/10.5694/mja2.51291
    Journal articles | 2022
    Peters R; Xu Y; Fitzgerald O; Aung HL; Beckett NS; Bulpitt CJ; Chalmers J; Forette F; Gong J; Harris K; Humburg P; Matthews FE; Staessen J; Thijs L; Tzourio C; Warwick J; Woodward M; Anderson CS, 2022, 'Blood pressure lowering and prevention of dementia: an individual patient data meta-analysis', European Heart Journal, 43, pp. 4980 - 4990, http://dx.doi.org/10.1093/eurheartj/ehac584
    Journal articles | 2022
    Peters R; Xu Y; Fitzgerald O; Aung HL; Beckett NS; Bulpitt CJ; Chalmers J; Forette F; Gong J; Harris K; Humburg P; Matthews FE; Staessen J; Thijs L; Tzourio C; Warwick J; Woodward M; Anderson CS, 2022, 'Blood pressure lowering and prevention of dementia: an individual patient data meta-analysis', European Heart Journal, 43, pp. 4980 - 4990, http://dx.doi.org/10.1093/eurheartj/ehac584
    Journal articles | 2021
    Fitzgerald O; Perez-Concha O; Gallego B; Saxena MK; Rudd L; Metke-Jimenez A; Jorm L, 2021, 'Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU', Journal of the American Medical Informatics Association, 28, pp. 1642 - 1650, http://dx.doi.org/10.1093/jamia/ocab060
    Journal articles | 2021
    Hanly M; Churches T; Fitzgerald O; Caterson I; MacIntyre CR; Jorm L, 2021, 'Modelling vaccination capacity at mass vaccination hubs and general practice clinics', , http://dx.doi.org/10.1101/2021.04.07.21255067
    Journal articles | 2021
    Hanly M; Churches T; Fitzgerald O; McIntyre R; Jorm L, 2021, 'Vaccinating Australia: How long will it take?', , http://dx.doi.org/10.1101/2021.02.02.21250979
    Journal articles | 2020
    Henry A; Arnott C; Makris A; Davis G; Hennessy A; Beech A; Pettit F; SE Homer C; Craig ME; Roberts L; Hyett J; Chambers G; Fitzgerald O; Gow M; Mann L; Challis D; Gale M; Ruhotas A; Kirwin E; Denney-Wilson E; Brown M, 2020, 'Blood pressure postpartum (BP2) RCT protocol: Follow-up and lifestyle behaviour change strategies in the first 12 months after hypertensive pregnancy', Pregnancy Hypertension, 22, pp. 1 - 6, http://dx.doi.org/10.1016/j.preghy.2020.07.001
    Journal articles | 2020
    Paul RC; Fitzgerald O; Lieberman D; Venetis C; Chambers GM, 2020, 'Cumulative live birth rates for women returning to ART treatment for a second ART-conceived child', Human Reproduction, 35, pp. 1432 - 1440, http://dx.doi.org/10.1093/humrep/deaa030
    Journal articles | 2018
    Ladanchuk T; Kwak S; Bates L; Parkin K; Harris K; Fitzgerald O; Lynch W; Moore KH, 2018, 'Vascular measures of atherosclerosis in detrusor overactivity and controls', Neurourology and Urodynamics, 37, pp. 2827 - 2832, http://dx.doi.org/10.1002/nau.23784
    Journal articles | 2017
    Chambers GM; Paul R; Harris K; Fitzgerald O; Boothroyd C; Rombaults L; Chapman MG; Jorm L, 2017, 'Cumulative live-birth rates after repeated assisted reproduction technology treatment cycles in Australian and New Zealand', Medical Journal of Australia, 207, pp. 114 - 118, http://dx.doi.org/10.5694/mja16.01435
    Journal articles | 2017
    Chambers GM; Paul RC; Harris K; Fitzgerald O; Boothroyd CV; Rombauts L; Chapman MG; Jorm L, 2017, 'Assisted reproductive technology in Australia and New Zealand: Cumulative live birth rates as measures of success', Medical Journal of Australia, 207, pp. 114 - 118, http://dx.doi.org/10.5694/mja16.01435
  • Preprints | 2024
    Fitzgerald O; Newman J; Rombauts L; Polyakov A; Chambers GM, 2024, Development of an IVF prediction model for donor oocytes: a retrospective analysis of 9,384 embryo transfers, , http://dx.doi.org/10.1101/2024.04.04.24305303
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Metke-Jimenez A; Rudd L; Jorm L, 2023, Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit, , http://arxiv.org/abs/2304.07025v1
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 2023, Curation and description of a blood glucose management and nutritional support cohort using the eICU collaborative research database, , http://dx.doi.org/10.1101/2023.04.20.23288845
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 2023, The relationship between hyperglycaemia on admission and patient outcome is modified by hyperlactatemia and diabetic status: a retrospective analysis of the eICU collaborative research database, , http://dx.doi.org/10.1101/2023.05.01.23289339
    Conference Abstracts | 2022
    Peters R; Xu Y; Fitzgerald O; Aung HL; Beckett NS; Bulpitt CJ; Chalmers J; Forette F; Gong J; Harris K; Humburg P; Matthews FE; Staessen J; Thijs L; Tzourio C; Warwick J; Woodward M; Anderson CS, 2022, 'Effects of blood pressure lowering for the prevention of dementia: meta‐analysis of individual patient data from five seminal randomised controlled trials involving 28008 participants', in Alzheimer's & Dementia, Wiley, Vol. 18, http://dx.doi.org/10.1002/alz.060056
    Conference Papers | 2020
    Law YJ; Zhang N; Paul R; Fitzgerald O; Harris K; Chambers G; Venetis C, 2020, 'Is the number of oocytes retrieved associated with time to conception leading to live birth? A population-based analysis of 221,073 cycles', in HUMAN REPRODUCTION, OXFORD UNIV PRESS, ELECTR NETWORK, pp. 40 - 40, presented at 36th Virtual Annual Meeting of the European-Society-of-Human-Reproduction-and-Embryology (ESHRE), ELECTR NETWORK, 05 July 2020 - 08 July 2020, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000552121500082&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Reports | 2019
    Newman J; Fitzgerald O; Paul R; Chambers G, 2019, Assisted reproductive technology in Australia and New Zealand 2017. Sydney: National Perinatal Epidemiology and Statistics Unit, the University of New South Wales
    Reports | 2018
    Fitzgerald O; Paul R; Harris K; Chambers G, 2018, Assisted reproductive technology in Australia and New Zealand 2016. Sydney: National Perinatal Epidemiology and Statistics Unit, the University of New South Wales
    Reports | 2018
    Fitzgerald O; Paul RC; Harris K; Chambers G, 2018, Assisted reproductive technology in Australia and New Zealand 2016, UNSW Sydney, Sydney
    Reports | 2017
    Fitzgerald O; Harris K; Paul RC; Chambers GM, 2017, Assisted reproductive technology in Australia and New Zealand 2015, UNSW Sydney, Sydney
    Reports | 2016
    Harris K; fitzgerald O; paul RC; macaldowie A; lee E; chambers GM, 2016, Assisted reproductive technology in Australia and New Zealand 2014, National Perinatal Epidemiology and Statistics Unit, UNSW, Sydney, https://npesu.unsw.edu.au/surveillance-reports

  • Development of prediction models for success from IVF treatment
  • Investigation of the relative importance of patient and treatment factors in the prediction of success from IVF treatment
  • Comparison of IVF treatment options (e.g. traditional IVF vs. ICSI) on patient outcomes
  • Interpretable machine learning methods
  • Transportability of clinical prediction models across populations and time