1 citations · 1 across the 3 of their papers we have counts for
3 papers
Enabling scalable clinical interpretation of ML-based phenotypes using real world data
Owen Parsons, Nathan E Barlow, Janie Baxter +4
The availability of large and deep electronic healthcare records (EHR) datasets has the potential to enable a better understanding of real-world patient journeys, and to identify n…
Compensating trajectory bias for unsupervised patient stratification using adversarial recurrent neural networks
Avelino Javer, Owen Parsons, Oliver Carr +6
Electronic healthcare records are an important source of information which can be used in patient stratification to discover novel disease phenotypes. However, they can be challeng…
Longitudinal patient stratification of electronic health records with flexible adjustment for clinical outcomes
Oliver Carr, Avelino Javer, Patrick Rockenschaub +2
The increase in availability of longitudinal electronic health record (EHR) data is leading to improved understanding of diseases and discovery of novel phenotypes. The majority of…