By Professor Louisa Jorm

Preprints

Gallego B; Huberts L; Yu J; Blake V; Jorm L; Liu L; Ooi S-Y, 2026, Explainable, personalised prediction of emergency readmission and mortality following hospitalisation in patients with heart failure, http://dx.doi.org/10.64898/2026.07.15.26358201

Kuo NI-H; Gallego B; Jorm L, 2026, From Hazard Functions to Language Space: Cox-Supervised Distillation of Survival Risk into a Large Language Model, http://dx.doi.org/10.48550/arxiv.2606.08945

Kuo NI-H; Gallego B; Jorm L, 2026, Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records, http://dx.doi.org/10.48550/arxiv.2606.08903

Kuo NI-H; Tania MH; Gallego B; Jorm L, 2026, PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modelling, http://dx.doi.org/10.48550/arxiv.2603.19299

Kuo NI-H; Gallego B; Jorm L, 2025, Limits of Generative Pre-Training in Structured EMR Trajectories with Irregular Sampling, http://dx.doi.org/10.48550/arxiv.2510.22878

Kuo NI-H; Gallego B; Jorm L, 2025, Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Records, http://dx.doi.org/10.48550/arxiv.2503.06096

Kuo NI-H; Gallego B; Jorm L, 2024, Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generation, http://dx.doi.org/10.48550/arxiv.2410.16811

Kuo NI-H; Gallego B; Jorm L, 2024, CK4Gen: A Knowledge Distillation Framework for Generating High-Utility Synthetic Survival Datasets in Healthcare, http://dx.doi.org/10.48550/arxiv.2410.16872

Bi B; Liu L; Lujic S; Jorm L; Perez-Concha O, 2024, Harmonising the Clinical Melody: Tuning Large Language Models for Hospital Course Summarisation in Clinical Coding, http://dx.doi.org/10.48550/arxiv.2409.14638

Quiroz JC; Brieger D; Jorm L; Sy RW; Hsu B; Gallego B, 2023, Predicting adverse outcomes following catheter ablation treatment for atrial fibrillation, http://dx.doi.org/10.48550/arxiv.2211.11965

Blake V; Jorm L; Yu J; Lee A; Gallego B; Ooi S-Y, 2023, The Cardiac Analytics and Innovation (CardiacAI) Data Repository: An Australian data resource for translational cardiovascular research, http://dx.doi.org/10.48550/arxiv.2304.09341

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://dx.doi.org/10.48550/arxiv.2304.07025

Kuo NI-H; Jorm L; Barbieri S, 2023, Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models, http://dx.doi.org/10.48550/arxiv.2303.12281

Kuo NI-H; Garcia F; Sönnerborg A; Zazzi M; Böhm M; Kaiser R; Polizzotto M; Jorm L; Barbieri S, 2023, Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV, http://dx.doi.org/10.48550/arxiv.2208.08655

Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models, http://dx.doi.org/10.48550/arxiv.2212.05857

Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models, http://dx.doi.org/10.48550/arxiv.2101.00146

Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding, http://dx.doi.org/10.48550/arxiv.2204.10716

Kuo NI-H; Polizzotto MN; Finfer S; Garcia F; Sönnerborg A; Zazzi M; Böhm M; Jorm L; Barbieri S, 2022, The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms, http://dx.doi.org/10.48550/arxiv.2203.06369

Butler DC; Jorm LR; Larkins S; Korda RJ, 2022, Area-level and individual-socioeconomic variation in use of GP and specialist services. A multilevel analysis using linked data, http://dx.doi.org/10.21203/rs.3.rs-1428954/v1

Kuo NI-H; Polizzotto M; Finfer S; Jorm L; Barbieri S, 2021, Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project, http://dx.doi.org/10.48550/arxiv.2112.03914

Quiroz JC; Brieger D; Jorm L; Sy RW; Falster MO; Gallego B, 2021, An observational study of clinical and health system factors associated with catheter ablation and early ablation treatment for atrial fibrillation in Australia, http://dx.doi.org/10.1101/2021.09.03.21263104

Barbieri S; Mehta S; Wu B; Bharat C; Poppe K; Jorm L; Jackson R, 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

Barbieri S; Kemp J; Perez-Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 2020, Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk, http://dx.doi.org/10.48550/arxiv.1905.08547

Walker AR; Venetis C; Opdal S; Anazodo AC; Hacker N; Chapman M; Jorm L; Norman RJ; Stern C; Sansom-Daly UM; Chambers GM; Vajdic CM, Assessing the effect of medically assisted reproduction on hormone-related cancers in women: an emulated target trial, http://dx.doi.org/10.1101/2025.11.16.25340364

Karystianis G; Adily A; Schofield PW; Greenberg D; Jorm L; Nenadic G; Butler T, Automated Analysis of Domestic Violence Police Reports to Explore Abuse Types and Victim Injuries: Text Mining Study (Preprint), http://dx.doi.org/10.2196/preprints.13067

Karystianis G; Adily A; Schofield P; Knight L; Galdon C; Greenberg D; Jorm L; Nenadic G; Butler T, Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives: Text Mining Study (Preprint), http://dx.doi.org/10.2196/preprints.11548

Walker AR; Vajdic CM; Anazodo AC; Hacker NF; Opdahl S; Chapman M; Sansom-Daly UM; Jorm L; Norman RJ; Stern C; Chambers GM; Venetis C, Childhood cancer in singletons conceived via medically assisted reproduction in Australia: a population-based cohort study, http://dx.doi.org/10.64898/2026.04.08.26350447

Chan JC; Hastings J; Tiernan G; Paterson J; Lovell N; Betbeder-Matibet L; Tung PKM; Pink S; Lanzeni D; Donovan T; Milat A; Jorm L; Mazariego C; Zhang C; Fontaine G; Best S; Kennedy G; Michie S; Lin F; Taylor N, Combining implementation and data sciences to accelerate evidence integration into healthcare - ImpleMATE, http://dx.doi.org/10.31219/osf.io/9qu7p_v1

Karystianis G; Adily A; Schofield P; Knight L; Galdon C; Greenberg D; Jorm L; Nenadic G; Butler T, Correction: Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives: Text Mining Study (Preprint), http://dx.doi.org/10.2196/preprints.13007

Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 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

Kuo NI-H; Perez-Concha O; Hanly M; Mnatzaganian E; Hao B; Di Sipio M; Yu G; Vanjara J; Valerie IC; de Oliveira Costa J; Churches T; Lujic S; Hegarty J; Jorm L; Barbieri S, Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project (Preprint), http://dx.doi.org/10.2196/preprints.51388

Quiroz JC; Chard T; Sa Z; Ritchie A; Jorm L; Gallego B, Extract, Transform, Load Framework for the Conversion of Health Databases to OMOP, http://dx.doi.org/10.1101/2021.04.08.21255178

Churches T; Jorm L, Flexible, Freely Available Stochastic Individual Contact Model for Exploring COVID-19 Intervention and Control Strategies: Development and Simulation (Preprint), http://dx.doi.org/10.2196/preprints.18965

Hanly M; Churches T; Fitzgerald O; Caterson I; MacIntyre CR; Jorm L, Modelling vaccination capacity at mass vaccination hubs and general practice clinics, http://dx.doi.org/10.1101/2021.04.07.21255067

Walker AR; Opdahl S; Venetis C; Jorm L; Hacker NF; Chapman M; Anazodo AC; Norman RJ; Stern C; Sansom-Daly UM; Chambers GM; Vajdic CM, Organised cancer screening among women who receive medically assisted reproduction treatments, http://dx.doi.org/10.64898/2026.07.05.26357336

Kuo NI-H; Tania MH; Gallego B; Jorm LR, PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modelling, http://dx.doi.org/10.64898/2026.03.19.26348848

Zoega H; Falster MO; Gillies MB; Litchfield M; Camacho X; Bruno C; Daniels B; Donnolley N; Havard A; Schaffer AL; Chambers G; Degenhardt L; Dobbins T; Gisev N; Ivers R; Jorm L; Liu B; Vajdic CM; Pearson S-A, The Medicines Intelligence Data Platform: A population-based data resource from New South Wales, Australia, http://dx.doi.org/10.1101/2024.04.29.24306520

Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 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

Stanaway F; Zhu L; McDonald B; Ravulo J; Dickson M; Nassar N; Yap ML; Jorm L; Aitken S; Kritharides L; Wilson A; Blyth FM; Schneider CH; Khalatbari-Soltani S; Hsu B; Allen L, Using linked Census data to categorise the population by ethnicity and enhance understanding of ethnic inequalities in health in Australia, http://dx.doi.org/10.31219/osf.io/5vg7t

Hanly M; Churches T; Fitzgerald O; McIntyre CR; Jorm L, Vaccinating Australia: How long will it take?, http://dx.doi.org/10.1101/2021.02.02.21250979

Liu L; Perez-Concha O; Nguyen A; Bennett V; Blake V; Gallego B; Jorm L, Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study (Preprint), http://dx.doi.org/10.2196/preprints.46322

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