Clinical Research Directory

Patient-Ventilator Dyssynchrony Detection With a Machine Learning Algorithm

Sponsor: University of Sao Paulo General Hospital

Summary

This is a diagnostic study aiming to compare accuracy to detect and classify patient-ventilator dyssynchronies by a machine learning algorithm, compared to the gold-standard defined as dyssynchronies diagnosed and classified by mechanical ventilator and esophageal pressure waveforms analyzed by experts. The main question of this study is: • Are patient-ventilator dyssynchronies accurately detected and classified by an artificial intelligence algorithm when compared to experts analyzing esophageal pressure and mechanical ventilator waveforms?

Official title: Automated Detection and Classification of Patient-Ventilator Dyssynchrony With a Machine Learning Algorithm

Key Details

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Interventions

Locations (1)