Papers › VoxMed: One-Step Respiratory Disease Classifier using Digital Stethoscope Sounds
VoxMed: One-Step Respiratory Disease Classifier using Digital Stethoscope Sounds
Paridhi Mundra, Manik Sharma, Yashwardhan Chaudhuri, Orchid Chetia Phukan, Arun Balaji Buduru
As respiratory illnesses become more common, it is crucial to quickly and accurately detect them to improve patient care. There is a need for improved diagnostic methods for immediate medical assessments for optimal patient outcomes. This paper introduces VoxMed, a UI-assisted one-step classifier that uses digital stethoscope recordings to diagnose respiratory diseases. It employs an Audio Spectrogram Transformer(AST) for feature extraction and a 1-D CNN-based architecture to classify respiratory diseases, offering professionals information regarding their patients respiratory health in seconds. We use the ICBHI dataset, which includes stethoscope recordings collected from patients in Greece and Portugal, to classify respiratory diseases. GitHub repository: https://github.com/Sample-User131001/VoxMed
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