7 citations · 16 across the 6 of their papers we have counts for
6 papers
Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models
Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri
This paper presents a novel approach to simulating electronic health records (EHRs) using diffusion probabilistic models (DPMs). Specifically, we demonstrate the effectiveness of D…
Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV
Nicholas I-Hsien Kuo, Federico Garcia, Anders Sönnerborg +6
Clinical data usually cannot be freely distributed due to their highly confidential nature and this hampers the development of machine learning in the healthcare domain. One way to…
The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms
Nicholas I-Hsien Kuo, Mark N. Polizzotto, Simon Finfer +6
In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not ope…
Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project
Nicholas I-Hsien Kuo, Mark Polizzotto, Simon Finfer +2
These two synthetic datasets comprise vital signs, laboratory test results, administered fluid boluses and vasopressors for 3,910 patients with acute hypotension and for 2,164 pati…
Learning to Continually Learn Rapidly from Few and Noisy Data
Nicholas I-Hsien Kuo, Mehrtash Harandi, Nicolas Fourrier +3
Neural networks suffer from catastrophic forgetting and are unable to sequentially learn new tasks without guaranteed stationarity in data distribution. Continual learning could be…
MTL2L: A Context Aware Neural Optimiser
Nicholas I-Hsien Kuo, Mehrtash Harandi, Nicolas Fourrier +3
Learning to learn (L2L) trains a meta-learner to assist the learning of a task-specific base learner. Previously, it was shown that a meta-learner could learn the direct rules to u…