5 papers
PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modelling
Nicholas I-Hsien Kuo, Marzia Hoque Tania, Blanca Gallego +1
In recent years, progress in medical informatics and machine learning has been accelerated by the availability of openly accessible benchmark datasets. However, patient-level elect…
Limits of Generative Pre-Training in Structured EMR Trajectories with Irregular Sampling
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
Foundation models refer to architectures trained on vast datasets using autoregressive pre-training from natural language processing to capture intricate patterns and motifs. They…
Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Records
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
Access to real-world healthcare data is limited by stringent privacy regulations and data imbalances, hindering advancements in research and clinical applications. Synthetic data p…
Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generation
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
Access to real clinical data is often restricted due to privacy obligations, creating significant barriers for healthcare research. Synthetic datasets provide a promising solution,…
CK4Gen: A Knowledge Distillation Framework for Generating High-Utility Synthetic Survival Datasets in Healthcare
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
Access to real clinical data is heavily restricted by privacy regulations, hindering both healthcare research and education. These constraints slow progress in developing new treat…