Asthma

Geomorphology

Cardiology

Sound (geography)

Computer science

Acoustics

Geology

Radiology

Auscultation

Physics

Stethoscope

Internal medicine

Artificial intelligence

Heart sounds

Respiratory system

Medicine

Crackles

Respiratory sounds

Lung

Sound analysis

Machine learning

Speech recognition

In modern medicine, every cardiac assessment or respiratory check-up includes an audio auscultation during which one the medical specialist listens to sounds from the patient body with different tools (stethoscope, sonography). This shows how important sound analysis is for heart and lungs disease detection. During the IeBRI 2017 challenge, a database of 920 records acquired from 126 subject, was used to find a method that predicted if a respiratory cycle contains, or not, adventitious sounds like crackles, wheezes or both of them. The team which submits the best results reached around 50% of correct detection. Using a machine learning approach with a boosted decisional tree model and more audio features leads to the same results. A new approach consists in creating a new model at the patient level, which is able to decide if a patient sounds sick or not, by taking as input the predicted results of the first classification model. This new model permits to reach 85% of good predictions and could be used as a tool for helping doctors to make better diagnosis.

Automatic Detection of Patient with Respiratory Diseases Using Lung Sound Analysis