Software using artificial intelligence for nodule and cancer detection in CT lung cancer screening: systematic review of test accuracy studies.

ABSTRACT:

Objectives

To examine the accuracy and impact of artificial intelligence (AI) software assistance in lung cancer screening using CT.

Methods

A systematic review of CE-marked, AI-based software for automated detection and analysis of nodules in CT lung cancer screening was conducted. Multiple databases including Medline, Embase and Cochrane CENTRAL were searched from 2012 to March 2023. Primary research reporting test accuracy or impact on reading time or clinical management was included. QUADAS-2 and QUADAS-C were used to assess risk of bias. We undertook narrative synthesis.

Results

Eleven studies evaluating six different AI-based software and reporting on 19 770 patients were eligible. All were at high risk of bias with multiple applicability concerns. Compared with

SUBMITTER: Geppert J 

PROVIDER: S-EPMC11503082 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature