jdcneto/Lung-Sound-Classification
This project is about classifying respiratory sounds using Attention and Vision Transformer on ICBHI dataset..
This project helps medical professionals automatically classify respiratory diseases by analyzing recorded lung sounds. It takes digital stethoscope recordings as input and identifies common conditions like asthma, pneumonia, or COPD. This tool is for clinicians, medical researchers, or healthcare providers who want to leverage machine learning for diagnostics.
No commits in the last 6 months.
Use this if you need to rapidly and accurately screen or diagnose respiratory conditions based on patient lung sound recordings.
Not ideal if you require real-time, in-person diagnostic support without recorded sound data.
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May 12, 2024
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