Methods for improving colorectal cancer annotation efficiency for artificial intelligence-observer training.

Background: Missing occult cancer lesions accounts for the most diagnostic errors in retrospective radiology reviews as early cancer can be small or subtle, making the lesions difficult to detect. Second-observer is the most effective technique for reducing these events and can be economically implemented with the advent of artificial intelligence (AI).

Aim: To achieve appropriate AI model training, a large annotated dataset is necessary to train the AI models.