This AI model is helping researchers detect disease based on coughs

"From cough to speech and even breath, the sounds our bodies make are filled with information about our health. Subtle clues hidden within these bioacoustic sounds hold the potential to revolutionize how we screen, diagnose, monitor and manage a wide range of health conditions like tuberculosis (TB) or chronic obstructive pulmonary disease (COPD). As researchers at Google, we recognize the potential of sound as a useful health signal, and also that smartphone microphones are widely accessible. To that end, we’ve been exploring ways to use AI to extract health insights from acoustic data.

Earlier this year, we introduced Health Acoustic Representations, or HeAR, a bioacoustic foundation model designed to help researchers build models that can listen to human sounds and flag early signs of disease. The Google Research team trained HeAR on 300 million pieces of audio data curated from a diverse and de-identified dataset, and we trained the cough model in particular using roughly 100 million cough sounds..." Lire la suite