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respiratory-sounds

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RespireNet is an innovative web-based application that harnesses the capabilities of deep learning and Mel-frequency cepstral coefficients (MFCC) as a feature extraction technique for accurate respiratory disease prediction. The primary objective of this user-friendly web application is to facilitate early detection.

  • Updated Aug 2, 2023
  • Python

Respiratory Sound Dataset is a refined collection of respiratory sound recordings sourced from Kaggle, designed for machine learning applications focused on detecting lung conditions such as wheezes and crackles. The dataset includes high-quality audio files, annotations, and metadata, making it suitable for research in respiratory health.

  • Updated Oct 4, 2024

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