This repo provides on overview of software tools we created to facilitate the use of (raw) ECG data in the context of scientific projects, mainly ML based. It further lists publications of our group in this context.
- Identifying Heart Failure in ECG Data With Artificial Intelligence
- A conceptual framework for establishing trust in real world intelligent systems
- Detecting myocardial scar using electrocardiogram data and deep neural networks
Python app with GUI and CLI to read and write raw ECG data in different formats (DAT, CSV, DCM, HL7, XML, ASC), to convert between formats and to preprocess the ECG data.
Authors: A. Krishna, S. Becker, M. Eichenlaub, D. Westermann, A. Loewe, T. Keller
Python app with GUI/CLI to extract raw data from 12-lead ECGs in PDF format and export the raw signal data as well as clinical metadata as CSV files.
Authors: J. Lang, N. Staubach, T. Keller
Authors: D. Grün, F. Rudolph, N. Gumpfer, J. Hannig, L.K. Elsner, B. von Jeinsen, C.W. Hamm, A. Rieth, M. Guckert, T. Keller.
Front Digit Health. 2021;2:584555.
Authors: M. Guckert, N. Gumpfer, J. Hannig, T. Keller, N. Urquhart
Cognitive Systems Research. 2021; 68:143-155.
Authors: N. Gumpfer, D. Grün, J. Hannig, T. Keller, M. Guckert
Biol Chem. 2020;402(8):911-923.
