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gathered ME-NBI images and patients' clinical information. Kato Y provided valuable advice regarding the technical information and managed the AI-assisted CNN-CAD system and analyzed the data in this manuscript. All authors gave final approval for publication. Ueyama H, Nagahara A, and Tada T take full responsibility for the work as a whole, including the study design, access to data, and the decision to submit and publish the manuscript.

Background and AimDetecting blood content in the gastrointestinal tract is one of the crucial applications of capsule endoscopy (CE). The suspected blood indicator (SBI) is a conventional tool used to automatically tag images depicting possible bleeding in the reading system. We aim to develop a deep learning‐based system to detect blood content in images and compare its performance with that of the SBI.MethodsWe trained a deep convolutional neural network (CNN) system, using 27 847 CE images (6503 images depicting blood content from 29 patients and 21 344 images of normal mucosa from 12 patients). We assessed its performance by calculating the area under the receiver operating characteristic curve (ROC‐AUC) and its sensitivity, specificity, and accuracy, using an independent test set of 10 208 small‐bowel images (208 images depicting blood content and 10 000 images of normal mucosa). The performance of the CNN was compared with that of the SBI, in individual image analysis, using the same test set.ResultsThe AUC for the detection of blood content was 0.9998. The sensitivity, specificity, and accuracy of the CNN were 96.63%, 99.96%, and 99.89%, respectively, at a cut‐off value of 0.5 for the probability score, which were significantly higher than those of the SBI (76.92%, 99.82%, and 99.35%, respectively). The trained CNN required 250 s to evaluate 10 208 test images.ConclusionsWe developed and tested the CNN‐based detection system for blood content in CE images. This system has the potential to outperform the SBI system, and the patient‐level analyses on larger studies are required.

The modified technique of EP for ampullary neoplasm contributed to lessening the occurrence of early complications. However, further refinement of this technique is necessary for improving the clinical outcome.