Application of artificial intelligence for diagnosis of pancreatic ductal adenocarcinoma by EUS: A systematic review and meta-analysis.

ABSTRACT: EUS-guided tissue acquisition carries certain risks from unnecessary needle puncture in the low-likelihood lesions. Artificial intelligence (AI) system may enable us to resolve these limitations. We aimed to assess the performance of AI-assisted diagnosis of pancreatic ductal adenocarcinoma (PDAC) by off-line evaluating the EUS images from different modes. The databases PubMed, EMBASE, SCOPUS, ISI, IEEE, and Association for Computing Machinery were systematically searched for relevant studies. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic curve were estimated using R software. Of 369 publications, 8 studies with a total of 870 PDAC patients were included. The pooled sensitivity and specificity of AI-assisted EUS were 0.91 (9

SUBMITTER: Prasoppokakorn T 

PROVIDER: S-EPMC8887033 | biostudies-literature | 2022 Jan-Feb

REPOSITORIES: biostudies-literature