Convolutional Neural Network for Respiratory Mechanics Estimation during Pressure Support Ventilation

Author:

Rodrigues Adriano S.,Maximo Marcos R.O.A.,Victor Marcus H.

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference20 articles.

1. Assessing effort and work of breathing;Bellani;Current opinion in critical care,2014

2. Detecting and correcting patient-ventilator asynchronies;Brochard;Critical Care,2016

3. Respiratory system dynamical mechanical properties: modeling in time and frequency domain;Carvalho;Biophysical reviews,2011

4. Chollet, F. et al. (2015). keras.

5. Performance of noninvasive ventilation masks in a lung model of copd exacerbation;de Macedo;Respiratory care,2019

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Parameter Identification of Respiratory Mechanics Based on Convolutional Neural Networks;2023 2nd International Conference on Automation, Robotics and Computer Engineering (ICARCE);2023-12-14

2. Development of Symbolic Signal Processing and Transformer Models for Predicting Respiratory System Mechanics in Mechanical Ventilation;2023 15th Biomedical Engineering International Conference (BMEiCON);2023-10-28

3. Mixed‐integer quadratic programming approach for noninvasive estimation of respiratory effort profile during pressure support ventilation;International Journal for Numerical Methods in Biomedical Engineering;2022-12-22

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