L Hao, T H G F Bakkes, A van Diepen, N Chennakeshava, R A Bouwman, A J R De Bie Dekker, P H Woerlee, F Mojoli, M Mischi, Y Shi, S Turco
BACKGROUND AND OBJECTIVE: Mechanical ventilation is a life-saving treatment for critically-ill patients. During treatment, patient-ventilator asynchrony (PVA) can occur, which can lead to pulmonary damage, complications, and higher mortality. While traditional detection methods for PVAs rely on visual inspection by clinicians, in recent years, machine learning models are being developed to detect PVAs automatically. However, training these models requires large labeled datasets, which are difficult to obtain, as labeling is a labour-intensive and time-consuming task, requiring clinical expertise...
April 12, 2024: Computer Methods and Programs in Biomedicine