23 citations · 43 across the 18 of their papers we have counts for
4 papers · 1 filter
Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment
Pawel Renc, Michal K. Grzeszczyk, Linglong Qian +3
We present Federated Timeline Synthesis (FTS), a novel framework for training generative foundation models across distributed timeseries data applied to electronic health records (…
Foundation Model of Electronic Medical Records for Adaptive Risk Estimation
Pawel Renc, Michal K. Grzeszczyk, Nassim Oufattole +9
Hospitals struggle to predict critical outcomes. Traditional early warning systems, like NEWS and MEWS, rely on static variables and fixed thresholds, limiting their adaptability,…
MISS: Multiclass Interpretable Scoring Systems
Michal K. Grzeszczyk, Tomasz Trzciński, Arkadiusz Sitek
In this work, we present a novel, machine-learning approach for constructing Multiclass Interpretable Scoring Systems (MISS) - a fully data-driven methodology for generating single…
Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load
Michal K. Grzeszczyk, Paulina Adamczyk, Sylwia Marek +8
The effectiveness of digital treatments can be measured by requiring patients to self-report their state through applications, however, it can be overwhelming and causes disengagem…