Identifying Heart Failure in ECG Data With Artificial Intelligence - A Meta-Analysis. - Dimitri Grün; Felix Rudolph; Nils Gumpfer; Jennifer Hannig; Laura K. Elsner; Beatrice von Jeinsen; Christian W. Hamm; Andreas Rieth; Michael Guckert; Till Keller (Frontiers Digit. Health, 2020)

An Experiment Environment for Definition, Training and Evaluation of Electrocardiogram-Based AI Models. - Nils Gumpfer; Joshua Prim; Dimitri Grün; Jennifer Hannig; Till Keller; Michael Guckert (AIME, 2021)

A Data Pipeline for Extraction and Processing of Electrocardiogram Recordings. - Joshua Prim; Tim Uhlemann; Nils Gumpfer; Dimitri Grün; Sebastian Wegener; Sabrina Krug; Jennifer Hannig; Till Keller; Michael Guckert (CinC, 2021)

An Ensemble Learning Approach to Detect Cardiac Abnormalities in ECG Data Irrespective of Lead Availability. - Tim Uhlemann; Joshua Prim; Nils Gumpfer; Dimitri Grün; Sebastian Wegener; Sabrina Krug; Jennifer Hannig; Till Keller; Michael Guckert (CinC, 2021)

A conceptual framework for establishing trust in real world intelligent systems. - Michael Guckert; Nils Gumpfer; Jennifer Hannig; Till Keller; Neil Urquhart (Cogn. Syst. Res., 2021)

SIGNed explanations: Unveiling relevant features by reducing bias. - Nils Gumpfer; Joshua Prim; Till Keller; Bernhard Seeger; Michael Guckert; Jennifer Hannig (Inf. Fusion, 2023)

The Stuff We Swim in: Regulation Alone Will Not Lead to Justifiable Trust in AI. - Simon T. Powers; Olena Linnyk; Michael Guckert; Jennifer Hannig; Jeremy Pitt; Neil Urquhart; Anikó Ekárt; Nils Gumpfer; The Anh Han; Peter R. Lewis 001; Stephen Marsh 001; Tim Weber (IEEE Technol. Soc. Mag., 2023)

Towards Trustworthy AI in Cardiology: A Comparative Analysis of Explainable AI Methods for Electrocardiogram Interpretation. - Nils Gumpfer; Borislav Dinov; Samuel Sossalla; Michael Guckert; Jennifer Hannig (AIME (2), 2024)