Multicentre study to assess the performance of an artificial intelligence instrument to support qualitative diagnosis of colorectal polyps.

ABSTRACT:

Objective

Computer-aided diagnosis (CAD) using artificial intelligence (AI) is expected to support the characterisation of colorectal lesions, which is clinically relevant for efficient colorectal cancer prevention. We conducted this study to assess the diagnostic performance of commercially available CAD systems.

Methods

This was a multicentre, prospective performance evaluation study. The endoscopist diagnosed polyps using white light imaging, followed by non-magnified blue light imaging (non-mBLI) and mBLI. AI subsequently assessed the lesions using non-mBLI (non-mAI), followed by mBLI (mAI). Eventually, endoscopists made the final diagnosis by integrating the AI diagnosis (AI+endoscopist). The primary endpoint was the accuracy of the AI diagnosis of neoplastic lesions. T

SUBMITTER: Sato K 

PROVIDER: S-EPMC11499753 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature