# BUET Multi-disease Heart Sound Dataset: A Comprehensive Auscultation Dataset for Developing Computer-Aided Diagnostic Systems

arXiv: https://arxiv.org/abs/2409.00724 · HTML: https://mlsanity.com/paper/2409.00724/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 36 references that are in the map.
- First posted on arXiv 1 Sep 2024.

## Builds on (most cited first, 1 of 1)

- [The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification](https://mlsanity.com/paper/2108.00813/) (2021)

## Built on by (most cited first, 2 of 2)

- [CaReAQA: A Cardiac and Respiratory Audio Question Answering Model for Open-Ended Diagnostic Reasoning](https://mlsanity.com/paper/2505.01199/) (2025)
- [StethoLM: Audio Language Model for Cardiopulmonary Analysis Across Clinical Tasks](https://mlsanity.com/paper/2603.00355/) (2026)

## Abstract (arXiv)

Cardiac auscultation, an integral tool in diagnosing cardiovascular diseases (CVDs), often relies on the subjective interpretation of clinicians, presenting a limitation in consistency and accuracy. Addressing this, we introduce the BUET Multi-disease Heart Sound (BMD-HS) dataset - a comprehensive and meticulously curated collection of heart sound recordings. This dataset, encompassing 864 recordings across five distinct classes of common heart sounds, represents a broad spectrum of valvular heart diseases, with a focus on diagnostically challenging cases. The standout feature of the BMD-HS dataset is its innovative multi-label annotation system, which captures a diverse range of diseases and unique disease states. This system significantly enhances the dataset's utility for developing advanced machine learning models in automated heart sound classification and diagnosis. By bridging the gap between traditional auscultation practices and contemporary data-driven diagnostic methods, the BMD-HS dataset is poised to revolutionize CVD diagnosis and management, providing an invaluable resource for the advancement of cardiac health research. The dataset is publicly available at this link: https://github.com/mHealthBuet/BMD-HS-Dataset.