  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
