Colon cancer is the third most common type of cancer in the Netherlands. Colon cancer is caused by the development of polyps to colon cancer. In order to detect colon cancer and pre-stages in a timely manner, the nationwide population cancer study was introduced in 2014 on the basis of a stool test. All people with a positive stool test are advised to undergo a coloscopy to view, remove and pathologically analyse polyps. The introduction of the population survey has resulted in an annual increase in the number of coloscopies, and this will only increase as a result of ageing. This results in long waiting lists and increasing costs. Currently, all polyps are being sent in for pathological research. About 80 to 90 % of all these polyps are small polyps with a minimal risk of colon cancer. Due to the high prevalence of small polyps with at that time minimal risk of colon cancer, the “optical diagnosis strategy” has been developed. When using the “optical diagnosis strategy”, small polyps in the colon are assessed by the high or low-security endoscopist. With high certainty, this strategy removes the small polyp and throws it away without the assessment of the pathologist. At the same time, small hyperplastic polyps are left in situ because they are considered innocent. However, if an endoscopist can make an optical diagnosis based on the appearance of the polyp only with low reliability, the polyp is sent to the pathologist. The optical diagnosis strategy leads to a significant reduction in the time and costs associated with coloscopy. In addition, the innovation contributes to reducing the risk of complications, as not every polyp has to be removed anymoreRecent studies show that the diagnostic accuracy of this “optical diagnosis strategy” is highly dependent on the training and experience of the endoscopist. In order to increase the accuracy of optical diagnosis, recent research on computer-aided diagnosis (CAD) has been carried out. Artificially intelligent programs can be developed that help endoscopists in the accurate classification of polyps. Despite the fact that artificial intelligence has shown potential as a diagnostic tool in recently published international studies, this technology is not yet being applied in an operational environment. In the light of the above, the project partners want to develop a classification tool, called POLAR, for polyps. Through the use of convolutional neural networks, the project partners intend to incorporate the golden standard of pathological analysis into a system in order to make a significant contribution to the reliability of the “optical diagnosis strategy” and the sustainability of Dutch care. The project contributes to an increase in valorisation and innovation within ZiuZ and relevant SMEs. The collaboration between ZiuZ, AMC/AMR, the MCL and the Society is a good example of a crossover between the ‘life science’ and ‘high-tech’ sector. The project also fits seamlessly with the societal challenge ‘health, demography and well-being’. With this project, project partners intend to push the boundaries of artificial intelligence applications in the healthcare sector. The techniques used by ZiuZ in the development of the classification tool, such as convolutional neural networks, are highly innovative techniques and constitute the current spearheads of artificial intelligence research. Especially in the medical world, these techniques are still very limited. Innovative is also the development of a tool that can classify polyps on a macroscopic level. Project partners expect to have a major impact on the reduction of healthcare costs in the Netherlands, Europe and the United States. First numerical analyses show that POLAR leads to savings in the tens of millions. In addition, the demand for artificial intelligence in healthcare is increasing according to research firm Gartner. With a new earning model, ZiuZ expects hospitals to board easily. From detailed calculations it is considered plausible that POLAR can achieve a turnover of EUR 6.1 million in 2025 and an increase in staff of 18.7 FTE. These are high-quality jobs.The most important aspect of sustainability is that there is an optimisation of the classification of polyps. This makes a significant contribution to keeping care affordable. In addition, the risk of complications decreases. It also leads to a much faster diagnosis for a group of patients, which reduces stress. The investigation will be carried out in accordance with the General Data Protection Regulation.