Artificial intelligence software for detecting unsuspected lung cancer on chest radiographs in an asymptomatic population.

ABSTRACT:

Background

Detecting clinically unsuspected lung cancer on chest radiographs is challenging. Artificial intelligence (AI) software that performs comparably to radiologists may serve as a useful tool.

Purpose

To evaluate the lung cancer detection performance of a commercially available AI software and to that of humans in a healthy population.

Materials and methods

This retrospective study used chest radiographs from the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial in the United States between November 1993 and July 2001 with pathological cancer diagnosis follow-up to 2009 (median 11.3 years). The software's predictions were compared to the PLCO radiologists' reads. A reader study was performed with a subset comparing the software to 3 experien

SUBMITTER: Kim T 

PROVIDER: S-EPMC12429178 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature