Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach
Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with
significant morbidity and mortality. The objective of this study was to evaluate the predictive …
significant morbidity and mortality. The objective of this study was to evaluate the predictive …
[HTML][HTML] Mortality prediction for patients with acute respiratory distress syndrome based on machine learning: a population-based study
Background Traditional scoring systems for patients' outcome prediction in intensive care
units such as Oxygenation Saturation Index (OSI) and Oxygenation Index (OI) may not …
units such as Oxygenation Saturation Index (OSI) and Oxygenation Index (OI) may not …
Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study
XF Ding, JB Li, HY Liang, ZY Wang, TT Jiao… - Journal of translational …, 2019 - Springer
Background To develop a machine learning model for predicting acute respiratory distress
syndrome (ARDS) events through commonly available parameters, including baseline …
syndrome (ARDS) events through commonly available parameters, including baseline …
[HTML][HTML] Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS)
S Le, E Pellegrini, A Green-Saxena, C Summers… - Journal of Critical …, 2020 - Elsevier
Purpose Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with
high mortality and associated morbidity. The objective of this study is to develop and …
high mortality and associated morbidity. The objective of this study is to develop and …
[HTML][HTML] Discriminating Acute Respiratory Distress Syndrome from other forms of respiratory failure via iterative machine learning
B Afshin-Pour, M Qiu, SH Vajargah, H Cheyne… - Intelligence-Based …, 2023 - Elsevier
Abstract Acute Respiratory Distress Syndrome (ARDS) is associated with high morbidity and
mortality. Identification of ARDS enables lung protective strategies, quality improvement …
mortality. Identification of ARDS enables lung protective strategies, quality improvement …
A systematic review of machine learning models for management, prediction and classification of ARDS
Aim Acute respiratory distress syndrome or ARDS is an acute, severe form of respiratory
failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements …
failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements …
Machine learning classifier models can identify acute respiratory distress syndrome phenotypes using readily available clinical data
P Sinha, MM Churpek, CS Calfee - American journal of respiratory …, 2020 - atsjournals.org
Rationale: Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with
differential clinical outcomes and responses to randomly assigned treatment have …
differential clinical outcomes and responses to randomly assigned treatment have …
Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model
Z Zhang - PeerJ, 2019 - peerj.com
Background Acute respiratory distress syndrome (ARDS) is associated with significantly
increased risk of death, and early risk stratification may help to choose the appropriate …
increased risk of death, and early risk stratification may help to choose the appropriate …
Machine learning classifier models can identify ARDS phenotypes using readily available clinical data
P Sinha, MM Churpek, CS Calfee - A15. CRITICAL CARE: BRAVE …, 2019 - atsjournals.org
Rationale Heterogeneity in acute respiratory distress syndrome (ARDS) is considered a key
factor in the multitude of negative randomized controlled trials (RCTs). Recently, in five RCT …
factor in the multitude of negative randomized controlled trials (RCTs). Recently, in five RCT …
Early prediction of moderate-to-severe condition of inhalation-induced acute respiratory distress syndrome via interpretable machine learning
J Wu, C Liu, L Xie, X Li, K Xiao, G Xie, F Xie - BMC Pulmonary Medicine, 2022 - Springer
Background Several studies have investigated the correlation between physiological
parameters and the risk of acute respiratory distress syndrome (ARDS), in addition, etiology …
parameters and the risk of acute respiratory distress syndrome (ARDS), in addition, etiology …