5 papers
From Statistical Fidelity to Clinical Consistency: Scalable Generation and Auditing of Synthetic Patient Trajectories
Guanglin Zhou, Armin Catic, Motahare Shabestari +4
Access to electronic health records (EHRs) for digital health research is often limited by privacy regulations and institutional barriers. Synthetic EHRs have been proposed as a wa…
On the entropies of subshifts of finite type on countable amenable groups
Sebastián Barbieri
Let be two countable amenable groups. We introduce the notion of group charts, which gives us a tool to embed an arbitrary -subshift into a -subshift. Using an entropy…
Generating Clinically Realistic EHR Data via a Hierarchy- and Semantics-Guided Transformer
Guanglin Zhou, Sebastiano Barbieri
Generating realistic synthetic electronic health records (EHRs) holds tremendous promise for accelerating healthcare research, facilitating AI model development and enhancing patie…
Self-simulable groups
Sebastián Barbieri, Mathieu Sablik, Ville Salo
We say that a finitely generated group is self-simulable if every effectively closed action of on a closed subset of is the topol…
Acquisition-Independent Deep Learning for Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations
Daan Kuppens, Sebastiano Barbieri, Daisy van den Berg +4
Deep learning has proven to be a suitable alternative to least-squares (LSQ) fitting for parameter estimation in various quantitative MRI (QMRI) models. However, current deep learn…