Background and Aim: It is necessary to establish universal methods for endoscopic diagnosis of Helicobacter pylori (HP) infection, such as computer‐aided diagnosis. In the present study, we propose a multistage diagnosis algorithm for HP infection.Methods: The aims of this study are to: (i) to construct an interpretable automatic diagnostic system using a support vector machine for HP infection; and (ii) to compare the diagnosis capability of our artificial intelligence (AI) system with that of endoscopists. Presence of an HP infection determined through linked color imaging (LCI) was learned through machine learning. Trained classifiers automatically diagnosed HP‐positive and ‐negative patients examined using LCI. We retrospectively analyzed the new images from 105 consecutive patients; 42 were HP positive, 46 were post‐eradication, and 17 were uninfected. Five endoscopic images per case taken from different areas were read into the AI system, and used in the HP diagnosis.Results: Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the diagnosis of HP infection using the AI system were 87.6%, 90.4%, 85.7%, 80.9%, and 93.1%, respectively. Accuracy of the AI system was higher than that of an inexperienced doctor, but there was no significant difference between the diagnosis of experienced physicians and the AI system.Conclusions: The AI system can diagnose an HP infection with significant accuracy. There remains room for improvement, particularly for the diagnosis of post‐eradication patients. By learning more images and considering a diagnosis algorithm for post‐eradication patients, our new AI system will provide diagnostic support, particularly to inexperienced physicians.

The visibility and diagnostic accuracy of early gastric cancer (EGC) after Helicobacter pylori (HP) eradication have been reported to improve using image-enhanced endoscopy (IEE) compared with white light imaging (WLI). The present study clarified the appropriate IEE for the detection and diagnosis of EGC in clinical settings. This prospective and cross-sectional study evaluated the visibility of EGC and endoscopic findings of gastric mucosa after successful HP eradication (n = 31) using videos with WLI and IEE. Three endoscopists evaluated high-definition videos in a randomized order. The mean visibility scores (MVSs) on linked color imaging (LCI) for atrophic border, intestinal metaplasia, map-like redness, and EGC were the highest among each modality (3.87 ± 0.34, 3.82 ± 0.49, 3.87 ± 0.50, and 3.35 ± 0.92, respectively). The MVSs with blue laser imaging (BLI) were highest for magnifying view of the demarcation line (DL), microsurface pattern (MSP), and microvascular pattern (MVP) for EGC (3.77 ± 0.49, 3.94 ± 0.25, and 3.92 ± 0.34, respectively). LCI had the highest visibility among findings of gastric mucosa and EGC after HP eradication, and BLI had the highest visibility of MVP, MSP, and DL in magnifying observation. These results suggest that LCI observation in the entire stomach and further magnifying BLI are the best methods for detecting and diagnosing EGCs after HP eradication, respectively.

Colonic mucus layers protect intestinal tissues against intestinal bacteria. We investigated the effects of dietary fiber and its metabolites on mucus production in the colonic mucosa. Mice were fed a partially hydrolyzed guar gum (PHGG)-containing diet and a fiber-free diet (FFD). The colon mucus layer, fecal short-chain fatty acid (SCFA) levels, and gut microbiota were evaluated. Mucin 2 (MUC2) expression was assessed in SCFA-treated LS174T cells. The role of AKT in MUC2 production was investigated. The mucus layer in the colonic epithelium was significantly increased in the PHGG group compared with that in the FFD group. In the PHGG group, an increase in Bacteroidetes in the stool was observed, and fecal acetate, butyrate, propionate, and succinate levels were significantly increased. However, MUC2 production was significantly increased only in succinate-stimulated LS174T cells. The succinate-induced MUC2 production was associated with AKT phosphorylation. Succinate mediated the PHGG-induced increase in the colon mucus layer.