8 papers
GARLIC: Graph Attention-based Relational Learning of Multivariate Time Series in Intensive Care
Ruirui Wang, Yanke Li, Manuel Günther +1
Healthcare data, such as Intensive Care Unit (ICU) records, comprise heterogeneous multivariate time series sampled at irregular intervals with pervasive missingness. However, clin…
ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening
Shreyasvi Natraj, Cyrus Achtari, Felice Gragnano +3
Electrocardiography (ECG) is one of the most widely used tests for diagnosing cardiovascular disease. Yet several remote clinics still utilize paper ECG printouts for their analysi…
On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series
Sharmita Dey, Diego Paez-Granados
Clinical time-series learning is routinely constrained by small, heterogeneous cohorts and protocol drift, while its downstream use spans both classification (e.g., pathology diagn…
A learning health system in Neurorehabilitation as a foundation for multimodal patient representation
Thomas Weikert, Eljas Roellin, Lukas Heumos +3
Neurological disorders represent a growing global health burden requiring long-term, interdisciplinary rehabilitation. Computational neurorehabilitation (compNR) - the use of data-…
FedSCS-XGB -- Federated Server-centric surrogate XGBoost for continual health monitoring
Felix Walger, Mehdi Ejtehadi, Anke Schmeink +1
Wearable sensors with local data processing can detect health threats early, enhance documentation, and support personalized therapy. In the context of spinal cord injury (SCI), wh…
KarmaTS: A Universal Simulation Platform for Multivariate Time Series with Functional Causal Dynamics
Haixin Li, Yanke Li, Diego Paez-Granados
We introduce KarmaTS, an interactive framework for constructing lag-indexed, executable spatiotemporal causal graphical models for multivariate time series (MTS) simulation. Motiva…