ArticleBMC gastroenterology2023
A single-center prospective study evaluating the usefulness of artificial intelligence for the diagnosis of esophageal squamous cell carcinoma in a real-time setting.
Article in BMC gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Review
- Artificial Intelligence-Assisted Confocal Laser Endomicroscopy for Predicting Invasion Depth of Superficial Esophageal Mucosal Lesions: A Cohort Study.Clinical and translational gastroenterology · 2026Article
- Article
- World Endoscopy Organization Position Statements for Artificial Intelligence in Endoscopic Diagnosis of Gastric Epithelial Neoplasia.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Review
- Opportunities and challenges of artificial intelligence-assisted endoscopy and high-quality data for esophageal squamous cell carcinoma.World journal of gastrointestinal oncology · 2026Review
- Artificial intelligence-assisted endoscopic diagnosis of esophageal squamous cell carcinoma.Frontiers in artificial intelligence · 2026Review
- Role of artificial intelligence in the detection and characterization of gastrointestinal premalignant and early malignant lesions.World journal of gastroenterology · 2025Review
- Artificial intelligence in endoscopic diagnosis of esophageal squamous cell carcinoma and precancerous lesions.Chinese medical journal · 2025Review
- Optimizing AI models to predict esophageal squamous cell carcinoma risk by incorporating small datasets of soft palate images.Scientific reports · 2025Article
- Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer.Thoracic cancer · 2024Article
- Novel milestones for early esophageal carcinoma: From bench to bed.World journal of gastrointestinal oncology · 2024Article
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral pre-clinical studies have reported the usefulness of artificial intelligence (AI) systems in the diagnosis of esophageal squamous cell carcinoma (ESCC). We conducted this study to evaluate the usefulness of an AI system for real-time diagnosis of ESCC in a clinical setting.
methodsThis study followed a single-center prospective single-arm non-inferiority design. Patients at high risk for ESCC were recruited and real-time diagnosis by the AI system was compared with that of endoscopists for lesions suspected to be ESCC. The primary outcomes were the diagnostic accuracy of the AI system and endoscopists. The secondary outcomes were sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and adverse events.
resultsA total of 237 lesions were evaluated. The accuracy, sensitivity, and specificity of the AI system were 80.6%, 68.2%, and 83.4%, respectively. The accuracy, sensitivity, and specificity of endoscopists were 85.7%, 61.4%, and 91.2%, respectively. The difference between the accuracy of the AI system and that of the endoscopists was - 5.1%, and the lower limit of the 90% confidence interval was less than the non-inferiority margin.
conclusionsThe non-inferiority of the AI system in comparison with endoscopists in the real-time diagnosis of ESCC in a clinical setting was not proven.
trial registrationJapan Registry of Clinical Trials (jRCTs052200015, 18/05/2020).
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