145 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- UNSW SydneyAU8 papers
- Australian e-Health Research CentreAU3 papers
- Australian Institute of Health and WelfareAU3 papers
- Commonwealth Scientific and Industrial Research OrganisationAU3 papers
- The University of SydneyAU2 papers
- Amsterdam UMC Location University of AmsterdamNL1 paper
- Cancer Center AmsterdamNL1 paper
- Concord Repatriation General HospitalAU1 paper
- HFR Freiburg KantonsspitalCH1 paper
- Institute of Cancer ResearchGB1 paper
- Macquarie UniversityAU1 paper
- Royal Marsden HospitalGB1 paper
9 papers
Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models
Leibo Liu, Oscar Perez-Concha, Anthony Nguyen +2
Background: Encouraged by the success of pretrained Transformer models in many natural language processing tasks, their use for International Classification of Diseases (ICD) codin…
Predicting adverse outcomes following catheter ablation treatment for atrial fibrillation
Juan C. Quiroz, David Brieger, Louisa Jorm +3
Objective: To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF). Methods: We used a lin…
Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding
Leibo Liu, Oscar Perez-Concha, Anthony Nguyen +2
International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical l…
Assessing the effectiveness of empirical calibration under different bias scenarios
Hon Hwang, Juan C Quiroz, Blanca Gallego
Background: Estimations of causal effects from observational data are subject to various sources of bias. One method of adjusting for the residual biases in the estimation of a tre…
Causal inference for observational longitudinal studies using deep survival models
Jie Zhu, Blanca Gallego
Causal inference for observational longitudinal studies often requires the accurate estimation of treatment effects on time-to-event outcomes in the presence of time-dependent pati…
De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models
Leibo Liu, Oscar Perez-Concha, Anthony Nguyen +2
Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information is mixed with Personally Identi…
Empirical Analysis of Zipf's Law, Power Law, and Lognormal Distributions in Medical Discharge Reports
Juan C Quiroz, Liliana Laranjo, Catalin Tufanaru +4
Bayesian modelling and statistical text analysis rely on informed probability priors to encourage good solutions. This paper empirically analyses whether text in medical discharge…
Targeted Estimation of Heterogeneous Treatment Effect in Observational Survival Analysis
Jie Zhu, Blanca Gallego
The aim of clinical effectiveness research using repositories of electronic health records is to identify what health interventions 'work best' in real-world settings. Since there…
Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI
Sebastiano Barbieri, Oliver J. Gurney-Champion, Remy Klaassen +1
Purpose: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighte…