Impact of User's Background Knowledge and Polyp Characteristics in Colonoscopy with Computer-Aided Detection.

ABSTRACT:

Background/aims

We investigated how interactions between humans and computer-aided detection (CADe) systems are influenced by the user's experience and polyp characteristics.

Methods

We developed a CADe system using YOLOv4, trained on 16,996 polyp images from 1,914 patients and 1,800 synthesized sessile serrated lesion (SSL) images. The performance of polyp detection with CADe assistance was evaluated using a computerized test module. Eighteen participants were grouped by colonoscopy experience (nurses, fellows, and experts). The value added by CADe based on the histopathology and detection difficulty of polyps were analyzed.

Results

The area under the curve for CADe was 0.87 (95% confidence interval [CI], 0.83 to 0.91). CADe assistance increased overall polyp detecti

SUBMITTER: Lee J 

PROVIDER: S-EPMC11391145 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature