Predicting Liberation from Mechanical Ventilation in the Intensive Care Unit
Team: Amaranth
- Program: Biomedical Engineering
- Course: EN.580.480 Precision Care Medicine
Project Description:
We aim to develop a model that can accurately predict independence from mechanical ventilation with an end-goal of supporting clinician’s informed decision-making, improving patient outcomes upon extubation, and decreasing ICU expenditures.
Project Photo:
A photo representing our project in relation with successful liberation and mechanical ventilation.
Project Video
Mechanical ventilation is a short-term intervention for acute respiratory failure, and is required by 20-40% of U.S. ICU admissions. The appropriate timing of patient liberation from this ventilatory support is critical to avoid complications and reduce healthcare costs. We aimed to create models that could accurately predict independence from mechanical ventilation, as they would be pivotal in supporting clinician’s informed decision-making, improving patient outcomes upon extubation, and decreasing ICU expenditures.