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  4. Ventilator Pressure Prediction Using a Regularized Regression Model
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Ventilator Pressure Prediction Using a Regularized Regression Model

Journal
Advances in Computational Intelligence
Lecture Notes in Computer Science
ISSN
0302-9743
1611-3349
Date Issued
2022
Author(s)
Arellano, Amaury
Facultad de Ingeniería - CampCM  
Bustamante, Erick
Facultad de Ingeniería - CampCM  
Garza, Carlos
Facultad de Ingeniería - CampCM  
Ponce, Hiram  
Facultad de Ingeniería - CampCM  
Type
text::book::book part
DOI
10.1007/978-3-031-19496-2_27
URL
https://scripta.up.edu.mx/handle/20.500.12552/4183
Abstract
The mechanical ventilation is one of the most frequent methods used in Intensive Care Units (ICUs) to improve the breathing of patients. During the early days of the COVID-19 pandemic, the use of mechanical ventilators has been crucial. In this work, we propose to build a Lasso regression model based on lung simulators for predicting the airway pressure in the respiratory circuit of ventilators while breathing. We model the whole breathing process in two separate states. After that, we analyze the feature importance in the regression model to better understand the ventilator pressure prediction. We anticipate this model would help improving the patient’s health and overcoming the cost barrier of new methods for mechanical ventilators. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Subjects

Airway pressure

Lasso regression

Machine learning

Mechanical ventilatio...

Simulators

Forecasting

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