Crowdsourced Respiratory Audio for Asthma and Healthy Subjects

Crowdsourced audio recordings of respiratory sounds filtered to include only Asthma and Healthy subjects. The dataset is hosted on Kaggle and is intended for binary classification tasks. Details on the number of samples, recording specifics, and collection methodology are not provided in the available metadata.

Use Cases

• Train a binary classifier to distinguish asthma from healthy subjects based on respiratory audio.
• Benchmark audio feature extraction and machine learning models for medical sound analysis.
• Explore the potential of crowdsourced audio data for preliminary respiratory health assessment.

Strengths

• Focuses on a specific binary classification task (Asthma vs. Healthy).
• Data is sourced from a crowdsourced initiative, which may increase sample diversity.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle

Collection Method

Crowdsourced collection, filtered to specific subject categories.