Research map: AI ‐Assisted Detection May Help Identify Visible but Missed Gastric Cancers During Routine Upper Endoscopy
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Papers in this map
Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images
· Toshiaki Hirasawa · 2018 · 748 citations · Cited by this paper
How to Define the Gastroesophageal Junction
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A Multicenter Pivotal Study on the Artificial Intelligence System for Neoplastic Lesions Detection in Upper Gastrointestinal Endoscopy
· Seiichiro Abe · 2025 · 11 citations · Cited by this paper
A Multicenter Prospective Study on the Safety and Efficacy of the New Low Axial Force Self‐Expandable Metallic Stent With Slim Delivery System for Malignant Colorectal Obstruction
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Variation in the rate of detection of minute and small early gastric cancers at diagnostic endoscopy may reflect the performance of individual endoscopists
· Daisuke Murakami · 2023 · 7 citations · Cited by this paper
Endoscopic Full‐Thickness Resection for Gastrointestinal Subepithelial and Epithelial Neoplasia: Current Status, Indications, and Technical and Oncological Challenges—A Multispecialty Perspective
· 2026 · Related
Impact of Artificial Intelligence‐Assisted Endoscopy on Screening for Upper Gastrointestinal Cancer in a Large‐Scale Health Screening Facility
· Chihiro Goto · 2026 · 2 citations · Cited by this paper
Gastric Per‐Oral Endoscopic Myotomy (G‐ POEM ) With Endoscopic Hand‐Suturing Closure
· 2026 · Related
How Does Artificial Intelligence‐Assisted Endoscopy Impact Upper Gastrointestinal Screening?
· Sho Suzuki · 2026 · 1 citation · Cited by this paper
Endoscopic Diagnosis and Treatment for Superficial Non‐Ampullary Duodenal Epithelial Tumors
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Clinical Outcomes of Endoscopic Full‐Thickness Resection Versus Laparoscopic and Endoscopic Cooperative Surgery: A Propensity Score‐Matched Comparative Study
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Endoscopic Papillectomy for Ampullary Tumors in Older Patients: Balancing Oncologic Benefit and Geriatric Risk
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Risk Stratification to Optimize Colorectal Cancer Screening: Development and Validation of a Decision‐Tree Model for Colonoscopy Prioritization
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