Machine learning modeling of lung mechanics: Assessing the variability and propagation of uncertainty in respiratory-system compliance and airway resistance-Reference-Cited by-同舟云学术

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Machine learning modeling of lung mechanics: Assessing the variability and propagation of uncertainty in respiratory-system compliance and airway resistance

Published:2024-01 Issue: Volume:243 Page:107888
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Barahona José^ORCID,Sahli Costabal Francisco^ORCID,Hurtado Daniel E.^ORCID

Funder

Agencia Nacional de Investigación y Desarrollo

Fondo Nacional de Desarrollo Científico y Tecnológico

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference74 articles.

1. A damaged-informed lung ventilator model for ventilator waveforms;Agrawal;Front. Physiol.,2021

2. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study;Petrilli;BMJ,2020

3. Baseline characteristics and outcomes of 1591 patients infected with Sars-cov-2 admitted to icus of the lombardy region, Italy;Grasselli;JAMA,2020

4. Lung mechanics of mechanically ventilated patients with Covid-19: analytics with high-granularity ventilator waveform data;Ge;Front. Med.,2020

5. An appraisal of respiratory system compliance in mechanically ventilated Covid-19 patients;Li Bassi;Crit. Care,2021

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