Frontiers

Integration of PCG spectrogram texture and deep features for the diagnosis of heart failure with preserved ejection fraction using heterogeneous stacking ensemble learning

This study proposes a novel heterogeneous stacking ensemble learning model for the fusion of phonocardiogram (PCG) spectrogram texture and deep features to detect heart failure with preserved ejection ...
Microsoft

High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training

The development of machine learning for cardiac care is severely hampered by privacy restrictions on sharing real patient electrocardiogram (ECG) data. Although generative AI offers a promising ...
IEEE

DMEL: The Differentiable Log-Mel Spectrogram as a Trainable Layer in Neural Networks

Abstract: In this paper we present the differentiable log-Mel spectrogram (DMEL) for audio classification. DMEL uses a Gaussian window, with a window length that can be jointly optimized with the ...
IEEE

A Study on the Generation of Spectrogram for the Detection of Venous Needle Dislodgement by Image Recognition Using Machine Learning

Abstract: The safety and quality of life for the approximately 350,000 dialysis patients in Japan are critically affected by the risk of unintentional needle dislodgement during hemodialysis, which ...