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To the Editor Recently, narrow-band imaging (NBI) has gained Food and Drug Administration 510(k) clearance for assessing the neoplastic potential of colorectal polyps. Using the NBI International Colorectal Endoscopic (NICE) classification or the Japan NBI Expert Team (JNET) classification during colonoscopy, endoscopists can make high-confidence histological predictions for diminutive polyps ≤5 mm. The NICE classification evaluates the pit patterns and microvessels of polyp surfaces and classifies them into three types: type 1, 2, and 3 for hyperplastic polyps or sessile serrated lesions, adenomas, and deep submucosal invasive cancers, respectively. According to the JNET classification, hyperplastic polyps or sessile serrated lesions, adenomas or carcinomas with low-grade structural atypia, highgrade intramucosal neoplasia or shallow submucosal invasive cancer, and deep submucosal invasive cancer are classified as types a, 2A, 2B, and 3, respectively. Although these classifications increase the histological predictive value, concerns still exist regarding disagreements among observers because of their subjective nature, which requires training and abundant endoscopic experience. The need for a reliable and objective system has fueled the development of software that automatically evaluates NBI colonoscopy images for histological prediction of polyps. Thus, comparing the efficacy of these newly developed technologies in NBI implementation is essential as a decision-making support tool for routine clinical practice. Racz et al. compared the accuracy of a developed artificial intelligence-based polyp histology prediction (AIPHP) method to the NICE classification and pathologic results. The AIPHP software was created using a machine learning method and measured five geometrical and color features of the image at optical maximum magnification. A total of 373 polyps were analyzed using AIPHP and NICE classifications. AIPHP’s accuracy was significantly higher for non-diminutive polyps than for diminutive polyps (92.2% vs. 82.1%, p=0.0032). In addition, the accuracy of the NICE classification was superior for non-diminutive polyps compared to diminutive polyps (99.4% vs. 95.2%, p=0.014). AIPHP correctly predicted neoplastic and hyperplastic polyps in 92.2% and 77.6% of the cases, respectively (p<0.0001). The accuracy of AIPHP tended to increase with increasing polyp size, whereas the NICE prediction was close to 100% for polyps of all sizes. A similar study was reported by a Japanese research team that investigated the endoscopic microvascular density (eMVD) using magnifying NBI images via image-editing software, especially focusing on epithelial tumors. eMVD was significantly higher in early colorectal carcinoma or high-grade dysplasia than in adenoma (0.152±0.079 vs. 0.119±0.059, p<0.050), implying continuous angiogenesis progression throughout the adenoma-carcinoma sequence. The best cutoff value for disThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.