A Usable GAN-Based Tool for Synthetic ECG Generation in Cardiac Amyloidosis Research
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| author | Speziale, Francesco Lomoio, Ugo Boccuto, Fabiola Veltri, Pierangelo Guzzi, Pietro Hiram |
| author_facet | Speziale, Francesco Lomoio, Ugo Boccuto, Fabiola Veltri, Pierangelo Guzzi, Pietro Hiram |
| contents | Cardiac amyloidosis (CA) is a rare and underdiagnosed infiltrative cardiomyopathy, and available datasets for machine-learning models are typically small, imbalanced and heterogeneous. This paper presents a Generative Adversarial Network (GAN) and a graphical command-line interface for generating realistic synthetic electrocardiogram (ECG) beats to support early diagnosis and patient stratification in CA. The tool is designed for usability, allowing clinical researchers to train class-specific generators once and then interactively produce large volumes of labelled synthetic beats that preserve the distribution of minority classes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08260 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Usable GAN-Based Tool for Synthetic ECG Generation in Cardiac Amyloidosis Research Speziale, Francesco Lomoio, Ugo Boccuto, Fabiola Veltri, Pierangelo Guzzi, Pietro Hiram Machine Learning Cardiac amyloidosis (CA) is a rare and underdiagnosed infiltrative cardiomyopathy, and available datasets for machine-learning models are typically small, imbalanced and heterogeneous. This paper presents a Generative Adversarial Network (GAN) and a graphical command-line interface for generating realistic synthetic electrocardiogram (ECG) beats to support early diagnosis and patient stratification in CA. The tool is designed for usability, allowing clinical researchers to train class-specific generators once and then interactively produce large volumes of labelled synthetic beats that preserve the distribution of minority classes. |
| title | A Usable GAN-Based Tool for Synthetic ECG Generation in Cardiac Amyloidosis Research |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2601.08260 |