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Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Code for: Deep Learning-Based Detection of Bowel Sound Events in Continuous Recordings

Authors: Yusuf, Celik;

Code for: Deep Learning-Based Detection of Bowel Sound Events in Continuous Recordings

Abstract

This repository contains the full implementation of the framework proposed in the paper: "Deep Learning-Based Detection of Bowel Sound Events in Continuous Recordings" The code includes model training, cross-validation, calibration, and post-processing steps used to reproduce the reported results. The implementation operates on precomputed HDF5 features. The raw audio preprocessing stage is described in the manuscript and is not included in this repository. The dataset used in this study is publicly available via Kaggle and is not redistributed here. Please refer to the original source for data access. This repository is provided to ensure reproducibility of the study.

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Keywords

biomedical signal processing, deep learning, bowel sounds

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average