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An improved YOLOv8 model, incorporating an illumination attention module, was developed for real-time instance segmentation and classification. The dataset comprised 9,820 benign ulcer images, 1,727 malignant ulcer images, and 15,791 normal mucosa images, split into training, testing, and validation sets at an 8:1:1 ratio. Performance was evaluated based on precision, recall, specificity, and processing latency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>On the validation set, the AI model achieved an overall precision, recall, and specificity of 0.91, 0.91, and 0.95, respectively. For malignant ulcer recognition specifically, the precision, recall, and specificity were 0.90, 0.91, and 0.99. The model demonstrated strong real-time performance with a latency of 8.84 ms per frame and a processing speed of 113 frames per second.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The developed AI model enables accurate, real-time discrimination between benign and malignant gastric ulcers during endoscopy. It holds potential to augment clinical decision-making, standardize diagnostic quality, and optimize biopsy strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12876-026-04848-9","type":"journal-article","created":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T04:53:56Z","timestamp":1777870436000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of a real-time AI model for differentiating benign and malignant gastric ulcers : a multicenter retrospective study"],"prefix":"10.1186","volume":"26","author":[{"given":"Yibo","family":"Tan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongjun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofei","family":"Bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyu","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,4]]},"reference":[{"issue":"10094","key":"4848_CR1","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1016\/S0140-6736(16)32404-7","volume":"390","author":"A Lanas","year":"2017","unstructured":"Lanas A, Chan FKL. 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The study protocol, including the request for waiver of informed consent, was initially reviewed and approved by the Institutional Review Board (The Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University; Approval No. 2024 Ethical Review No.129). The requirement for informed consent was waived by the Institutional Review Boards due to the retrospective nature of the study and the use of fully anonymized data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"378"}}