Louisa Jorm
Orcid: 0000-0003-0390-661X
According to our database1,
Louisa Jorm
authored at least 17 papers
between 2019 and 2023.
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Bibliography
2023
Continuous time recurrent neural networks: Overview and benchmarking at forecasting blood glucose in the intensive care unit.
J. Biomed. Informatics, October, 2023
Artif. Intell. Medicine, October, 2023
Generating synthetic clinical data that capture class imbalanced distributions with generative adversarial networks: Example using antiretroviral therapy for HIV.
J. Biomed. Informatics, August, 2023
The Cardiac Analytics and Innovation (CardiacAI) Data Repository: An Australian data resource for translational cardiovascular research.
CoRR, 2023
Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit.
CoRR, 2023
Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models.
CoRR, 2023
2022
De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.
J. Biomed. Informatics, 2022
J. Biomed. Informatics, 2022
CoRR, 2022
Predicting adverse outcomes following catheter ablation treatment for atrial fibrillation.
CoRR, 2022
Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV.
CoRR, 2022
The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms.
CoRR, 2022
2021
Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU.
J. Am. Medical Informatics Assoc., 2021
Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project.
CoRR, 2021
De-identifying Hospital Discharge Summaries: An End-to-End Framework using Ensemble of De-Identifiers.
CoRR, 2021
2020
Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.
CoRR, 2020
2019
A Deep Representation of Longitudinal EMR Data Used for Predicting Readmission to the ICU and Describing Patients-at-Risk.
CoRR, 2019