Respiratory Insufficiency

Respiratory insufficiency (RI) detection is a critical area of research focusing on developing accurate and efficient diagnostic tools. Current efforts leverage artificial intelligence, particularly deep learning models like convolutional neural networks (CNNs) and transformers, to analyze audio signals (speech) as biomarkers for RI. While these models demonstrate high accuracy in classifying the presence of RI in some datasets, generalizability across diverse RI causes remains a challenge, highlighting the need for more robust and broadly applicable algorithms. The successful development of such tools could significantly improve early diagnosis and management of RI, impacting patient care and healthcare resource allocation.