Dominik Linz

According to our database, Dominik Linz authored at least 5 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Pooling cohorts for deep learning analysis: a potential source of bias for electrocardiogram analysis.

Marie Mørch-Pedersen, Malene Nørregaard, Claus Graff, Oliver B. Vad, Pia R. Lundegaard, Jesper Hastrup Svendsen, Torben Hansen, Allan Linneberg, Peter G. Jørgensen, Magnus T. Jensen, Peter Rossing, Christina Ellervik, Dominik Linz, Vajira Thambawita, Mary M. Maleckar, Michael A. Riegler, Jørgen K. Kanters, Jonas Isaksen

Biomed. Signal Process. Control., 2026

2025

Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.

Martin Manninger, Ingmar Lercher, Astrid N. L. Hermans, Jonas Isaksen, Anton J. Prassl, Andreas Zirlik, Kevin Vernooy, Sevasti-Maria Chaldoupi, Justin Luermans, Rachel M. A. ter Bekke, Jørgen K. Kanters, Gernot Plank, Daniel Scherr, Thomas Pock, Dominik Linz

Comput. Methods Programs Biomed., 2025

Raw photoplethysmogram waveforms versus peak-to-peak intervals for machine learning detection of atrial fibrillation: Does waveform matter?

Jonas Isaksen, Bolette Arildsen, Cathrine Lind, Malene Nørregaard, Kevin Vernooy, Ulrich Schotten, Thomas Jespersen, Konstanze Betz, Astrid N. L. Hermans, Jørgen K. Kanters, Dominik Linz

Comput. Methods Programs Biomed., 2025

2019

Beamforming-inspired Spatial Filtering Technique for Intracardiac Electrograms.

Simanto Saha, Dominik Linz, Prashanthan Sanders, Mathias Baumert

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

A Ventricular Far-Field Artefact Filtering Technique for Atrial Electrograms.

Simanto Saha, Simon Hartmann, Dominik Linz, Prashanthan Sanders, Mathias Baumert

Proceedings of the 46th Computing in Cardiology, 2019