The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect adenoma prevalence rate, estimated to be greater than 50% among the screening-age population. Yet the rate of adenoma detection by colonoscopists varies from 7% to 53%. It is estimated that every 1% increase in ADR reduces the risk of interval colorectal cancers by 3-6%. New strategies are needed to increase the ADR during colonoscopy. We tested the ability of computer-assisted image analysis, with convolutional neural networks (a deep learning model for image analysis), to improve polyp detection, a surrogate of ADR.