Progression in the application of machine learning in acute respiratory distress syndrome / 中华危重病急救医学
Chinese Critical Care Medicine
;
(12): 662-664, 2023.
Article
Dans Chinois
| WPRIM
| ID: wpr-982650
ABSTRACT
Acute respiratory distress syndrome (ARDS) is a clinical syndrome defined by acute onset of hypoxemia and bilateral pulmonary opacities not fully explained by cardiac failure or volume overload. At present, there is no specific drug treatment for ARDS, and the mortality rate is high. The reason may be that ARDS has rapid onset, rapid progression, complex etiology, and great heterogeneity of clinical manifestations and treatment. Compared with traditional data analysis, machine learning algorithms can automatically analyze and obtain rules from complex data and interpret them to assist clinical decision making. This review aims to provide a brief overview of the machine learning progression in ARDS clinical phenotype, onset prediction, prognosis stratification, and interpretable machine learning in recent years, in order to provide reference for clinical.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Pronostic
/
Syndrome de détresse respiratoire du nouveau-né
/
Apprentissage machine
/
Hypoxie
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Chinese Critical Care Medicine
Année:
2023
Type:
Article
Documents relatifs à ce sujet
MEDLINE
...
LILACS
LIS