{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T08:09:00Z","timestamp":1783930140219,"version":"3.55.0"},"reference-count":52,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T00:00:00Z","timestamp":1783814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: Esophageal cancer is a highly lethal malignancy, the prognosis of which depends largely on early diagnosis. Artificial intelligence (AI) has emerged as a promising tool to enhance endoscopic detection and characterization of early esophageal cancer. This scoping review aims to map and synthesize the available evidence regarding the diagnostic performance and clinical utility of artificial intelligence systems applied to upper gastrointestinal endoscopy for the detection and characterization of premalignant squamous lesions and early-stage esophageal squamous cell carcinoma (ESCC). Methods: A scoping review was conducted according to Arksey and O\u2019Malley, Levac, Joanna Briggs Institute, and PRISMA-ScR recommendations. The review question focused on patients with premalignant lesions or early ESCC, artificial intelligence-based diagnostic systems, and upper gastrointestinal endoscopy. Searches were performed in PubMed, Scopus, and Embase. Original studies reporting sensitivity, specificity, accuracy, AUC, or F1-score were included. Results: A total of 30 publications were included, consisting mainly of retrospective observational and diagnostic test studies (26\/30; 86.7%), followed by randomized clinical trials (3\/30; 10.0%) and a multicenter validation study (1\/30; 3.3%). The studies were predominantly from China (18\/30; 60%), followed by Japan (8\/30; 26.7%), Taiwan (3\/30; 10%), and the United Kingdom + Taiwan (1\/30; 3%). Automatic lesion detection was predominant (21\/30; 70.0%), followed by diagnostic classification (11\/30; 36.7%), while segmentation (3\/30; 10.0%), histological prediction (2\/30; 6.7%), estimation of invasion depth (3\/30; 10.0%), and lesion delineation (1\/30; 3.3%) were evaluated less frequently, and in some cases combined within the same model. The most used endoscopic imaging modalities were narrow-band imaging (23\/30; 76.7%) and white light endoscopy (20\/30; 66.7%), followed by magnifying endoscopy with narrow-band imaging (5\/30; 16.7%), blue light imaging (2\/30; 6.7%), and hyperspectral imaging (1\/30; 3.3%). Conclusions: Available studies suggest that AI has the potential to achieve high diagnostic performance under controlled conditions. However, the current evidence is derived predominantly from single-center retrospective studies using selected high-quality static images, with limited external, prospective, and real-world validation.<\/jats:p>","DOI":"10.3390\/cancers18142235","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:28:27Z","timestamp":1783927707000},"page":"2235","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Applications of Artificial Intelligence in the Endoscopic Detection and Characterization of Early Esophageal Squamous Cell Carcinoma: A Scoping Review"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1807-0221","authenticated-orcid":false,"given":"Faure","family":"Rodr\u00edguez-Vel\u00e1squez","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, School of Medicine, Universidad de La Sabana, Ch\u00eda 250001, Colombia"},{"name":"Endogut Research Group, Bogot\u00e1 111121, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e9s","family":"Montoya-Dur\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, School of Medicine, Universidad de La Sabana, Ch\u00eda 250001, Colombia"},{"name":"Gastroenterology Service, Fundaci\u00f3n Cl\u00ednica Shaio, Bogot\u00e1 111121, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1196-7056","authenticated-orcid":false,"given":"Nicole","family":"Bonilla","sequence":"additional","affiliation":[{"name":"School of Medicine, Universidad de La Sabana, Ch\u00eda 250001, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacobo","family":"Echeverri-Hoyos","sequence":"additional","affiliation":[{"name":"School of Medicine, Instituci\u00f3n Universitaria Visi\u00f3n de las Am\u00e9ricas, Pereira 660000, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaime A.","family":"Echeverri-Franco","sequence":"additional","affiliation":[{"name":"Pulmonology, Cl\u00ednica de Alta Tecnolog\u00eda Onc\u00f3logos del Occidente, Pereira 660000, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7243-2238","authenticated-orcid":false,"given":"Eduardo","family":"Tuta-Quintero","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Internal Medicine, School of Medicine, Universidad de La Sabana, Ch\u00eda 250001, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1053\/j.gastro.2022.05.054","article-title":"The global landscape of esophageal squamous cell carcinoma and esophageal adenocarcinoma incidence and mortality in 2020 and projections to 2040: New estimates from GLOBOCAN 2020","volume":"163","author":"Morgan","year":"2022","journal-title":"Gastroenterology"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Shen, J., Lu, K., Liu, F., Chen, X., Chen, Q., Wu, B., Wang, H., Ge, P., Han, G., and Wang, F. 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