NIH Reporter #5K23HD113816-03

Predicting Clinical Deterioration in Mechanically Ventilated Children using High-Frequency Physiologic Data

This award supports research to develop and implement predictive models for clinical deterioration in mechanically ventilated children using high-frequency physiological data and advanced machine learning, aiming to improve patient outcomes in pediatric intensive care units.

Description

A project to derive, validate, and implement machine learning-based prediction models of new or worsening cardiorespiratory dysfunction in critically ill children requiring mechanical ventilation, leveraging high-frequency physiological data and clinical variables.

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