XAI Interpretation of Graph Neural Network Models: Towards Trustworthy Diagnosis of Bundle Branch Blocks

Introduction: The application of Artificial Intelligence (AI) in clinical research is progressing rapidly. In the context of electrocardiogram (ECG) analysis, conventional approaches treat signals as waveforms or tabular data. Graph Neural Networks (GNNs) are particularly well-suited for modelling data [for full text, please go to the a.m. URL]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-11-03
DOI
https://doi.org/10.3205/25gmds130
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

XAI Interpretation of Graph Neural Network Models: Towards Trustworthy Diagnosis of Bundle Branch Blocks

German Medical Science (German Research Foundation)
ECG Monitoring and Analysis
article

XAI Interpretation of Graph Neural Network Models: Towards Trustworthy Diagnosis of Bundle Branch Blocks

article en

Abstract

Introduction: The application of Artificial Intelligence (AI) in clinical research is progressing rapidly. In the context of electrocardiogram (ECG) analysis, conventional approaches treat signals as waveforms or tabular data. Graph Neural Networks (GNNs) are particularly well-suited for modelling data [for full text, please go to the a.m. URL]

German Medical Science (German Research Foundation)
Justus-Liebig-Universität Gießen (DE), Universitätsmedizin Göttingen (DE), University of Göttingen (DE), Technical University of Denmark (DK)
Openalex Percentile: Top 35%
ECG Monitoring and Analysis
DOIOpen Access PDFOpenAlex
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