A diffusion model generates synthetic phonocardiogram clips that retain some normal/abnormal discriminative structure (82.8% classifier accuracy) but show reduced envelope periodicity and increased burstiness relative to real clips from the PhysioNet 2016 dataset.
Synthesis of normal heart sounds using generative adversarial networks and empirical wavelet trans- form,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
A diffusion model generates synthetic phonocardiogram clips that retain some normal/abnormal discriminative structure (82.8% classifier accuracy) but show reduced envelope periodicity and increased burstiness relative to real clips from the PhysioNet 2016 dataset.