Eunice Kennedy Shriver National Institute of Child Health and Human Development 5K23HD113816-02

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

The project involves deriving and validating machine learning-based prediction models for clinical deterioration in mechanically ventilated children, focusing on high-frequency physiological data, and includes designing for implementation and usability testing to ensure clinical acceptance and utility.

Description

This NIH grant supports research on machine learning models to predict clinical deterioration in critically ill children, leveraging high-frequency physiological data and clinical variables. The project aims to develop, validate, and implement predictive models to improve patient outcomes.

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