Machine Learning Models for Predicting In-Hospital Mortality in Acute Aortic Dissection Patients.

ABSTRACT: Background: Acute aortic dissection is a potentially fatal cardiovascular disorder associated with high mortality. However, current predictive models show a limited ability to efficiently and flexibly detect this mortality risk, and have been unable to discover a relationship between the mortality rate and certain variables. Thus, this study takes an artificial intelligence approach, whereby clinical data-driven machine learning was utilized to predict the in-hospital mortality of acute aortic dissection. Methods: Patients diagnosed with acute aortic dissection between January 2015 to December 2018 were voluntarily enrolled from the Second Xiangya Hospital of Central South University in the study. The diagnosis was defined by magnetic resonance angiography or computed tomogra

SUBMITTER: Guo T 

PROVIDER: S-EPMC8484712 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature