7 papers
From Hazard Functions to Language Space: Cox-Supervised Distillation of Survival Risk into a Large Language Model
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
We investigate whether information about time-to-event risk estimated by a Cox proportional hazards model can be transferred into a generative large language model. We propose a te…
Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records
Nicholas I-Hsien Kuo, Blanca Gallego, Louisa Jorm
Synthetic healthcare data are widely proposed as privacy-preserving substitutes for real patient data, yet their evaluation remains dominated by statistical similarity and predicti…
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,…