Advances in machine learning in the diagnosis and treatment of acute respiratory distress syndrome
10.3969/j.issn.1008-9691.2023.05.024
- VernacularTitle:机器学习在急性呼吸窘迫综合征诊治中的研究进展
- Author:
Mingkun YANG
1
;
Weihang HU
;
Jing YAN
Author Information
1. 浙江中医药大学第二临床医学院,浙江杭州 310053
- Keywords:
Machine learning;
Acute respiratory distress syndrome;
Diagnosis;
Treatment
- From:
Chinese Journal of Integrated Traditional and Western Medicine in Intensive and Critical Care
2023;30(5):632-635
- CountryChina
- Language:Chinese
-
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.
