Advances in machine learning in the diagnosis and treatment of acute respiratory distress syndrome / 中国中西医结合急救杂志

ABSTRACT

Acute respiratory distress syndrome(ARDS)is a highly fatal syndrome in the intensive care unit(ICU),with a mortality rate of up to 40%.Early identification and treatment of ARDS are essential to improve the prognosis.Machine learning,the core of artificial intelligence and data science,is a set of computer tools designed to acquire new knowledge from existing data,which can assist medical staff in making clinical decisions.In recent years,machine learning has been increasingly used in the clinical diagnosis,precision treatment,and prognosis assessment of ARDS,which is expected to generate new ideas for diagnosing and treating ARDS.This article summarizes the application of machine learning in the clinical diagnosis of ARDS,classification of ARDS,treatment of ARDS,prognosis evaluation of ARDS,and the shortcomings of machine learning in the application of ARDS to explore the research progress of machine learning in diagnosing and treating ARDS and provide directions for further research.