Audio Cough Analysis by Parametric Modelling of Weighted Spectrograms to Interpret the Output of Convolutional Neural Networks.

This study explores the feasibility of employing eXplainable Artificial Intelligence (XAI) methodologies for the analysis of cough patterns in respiratory diseases. A cohort of 20 adult patients, all presenting persistent cough as a symptom of respiratory disease, was monitored for 24 hours using a smartphone. The audio signals underwent frequency domain transformation to yield 1-second spectrograms, subsequently processed by a CNN to detect cough events.

[Validation of half-night polysomnography for sleep apnea/hypoapnea syndrome].

Unlabelled: A diagnosis of sleep apnea/hypopnea syndrome (SAHS) is based on clinical signs and nighttime polysomnograms. Brief polysomnography has been proposed as an alternative to all-night recording.

Objectives: The aim of this study was to determine whether a polysomnograms obtained during the first half of the night is sufficient for establishing a diagnosis of SAHS and to determine the correlation between polysomnographic variables recorded during the first four hours (half the study time) with those recorded over the full eight hours (full study time), as well as to determine diagnostic agreement.