Aortic Dissection Auxiliary Diagnosis Model and Applied Research Based on Ensemble Learning.

ABSTRACT: Aortic dissection (AD), a dangerous disease threatening to human beings, has a hidden onset and rapid progression and has few effective methods in its early diagnosis. At present, although CT angiography acts as the gold standard on AD diagnosis, it is so expensive and time-consuming that it can hardly offer practical help to patients. Meanwhile, the artificial intelligence technology may provide a cheap but effective approach to building an auxiliary diagnosis model for improving the early AD diagnosis rate by taking advantage of the data of the general conditions of AD patients, such as the data about the basic inspection information. Therefore, this study proposes to hybrid five types of machine learning operators into an integrated diagnosis model, as an auxiliary diagnostic approach,

SUBMITTER: Luo J 

PROVIDER: S-EPMC8733407 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature