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Nils Gumpfer

A Systematic Review on Explainable AI for Time Series Classification
Beyond Local Inspection: Global, Guideline-Grounded Evaluation of Post-hoc XAI Methods for ECG Classification
Resting electrocardiographic and pulse-wave deep learning identifies exaggerated exercise blood pressure response in elite athletes
Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review
Towards Trustworthy AI in Cardiology: A Comparative Analysis of Explainable AI Methods for Electrocardiogram Interpretation
The Stuff We Swim in: Regulation Alone Will Not Lead to Justifiable Trust in AI
SIGNed explanations: Unveiling relevant features by reducing bias
A Data Pipeline for Extraction and Processing of Electrocardiogram Recordings
An Ensemble Learning Approach to Detect Cardiac Abnormalities in ECG Data Irrespective of Lead Availability
A conceptual framework for establishing trust in real world intelligent systems
Detecting myocardial scar using electrocardiogram data and deep neural networks
Identifying Heart Failure in ECG Data With Artificial Intelligence—A Meta-Analysis
An Experiment Environment for Definition, Training and Evaluation of Electrocardiogram-Based AI Models

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