BACKGROUND: Anastomotic stenosis following esophagojejunostomy reconstruction by the overlap method with absorbable barbed sutures occurs only rarely in patients who have undergone laparoscopic surgery. We report anastomotic stenosis by the overlap m...
Journal of gastroenterology and hepatology
Nov 25, 2021
BACKGROUND AND AIM: Recently, artificial intelligence (AI) has been used in endoscopic examination and is expected to help in endoscopic diagnosis. We evaluated the feasibility of AI using convolutional neural network (CNN) systems for evaluating the...
Journal of clinical laboratory analysis
Nov 22, 2021
BACKGROUND AND AIM: Gastrointestinal endoscopy and biopsy-based pathological findings are needed to diagnose early gastric cancer. However, the information of biopsy specimen is limited because of the topical procedure; therefore, pathology doctors s...
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...
Our paper highlights the use of artificial intelligence (AI) in oesophageal and gastric malignancies with acceptable levels of accuracy for both diagnostic and surveillance purposes. Here, we comment on the past, present and future work necessary for...
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
BACKGROUND: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Oct 15, 2021
BACKGROUND: This study aimed to prevent missing gastric cancer and point out low-quality images by developing a double-check support system (DCSS) for esophagogastroduodenoscopy (EGD) still images using artificial intelligence.
OBJECTIVE: To evaluate the impact of robotic technology on the learning curve for robot-assisted gastrectomy in the initial clinical application stage and to compare RAG with laparoscopic-assisted gastrectomy using a short-term evaluation.
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