Development and validation of the diagnostic accuracy of artificial intelligence-assisted ultrasound in the classification of splenic trauma.

ABSTRACT:

Background

Spleen is the most vulnerable organ in abdominal trauma. Ultrasound (US) has become an important examination method for splenic trauma. However, the sensitivity of routine US in the diagnosis of splenic trauma is low. Contrast-enhanced ultrasound (CEUS) can improve the sensitivity, but it also has some limitations. This study sought to explore the application value of artificial intelligence (AI)-assisted US in the classification of splenic trauma.

Methods

The splenic injuries of Bama miniature pigs were established. A large number of ultrasonic images were collected. Then, 3-fold cross validation (CV) was used to establish the animal models. Next, clinical ultrasonic images were collected at multiple centers. All injuries were diagnosed by CEUS, enhanced CT or su

SUBMITTER: Jiang X 

PROVIDER: S-EPMC9622480 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature