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Stomach Neoplasms

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Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study.

EBioMedicine
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.

Development and evaluation of a double-check support system using artificial intelligence in endoscopic screening for gastric cancer.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
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.

The impact of robotic technology on the learning curve for robot-assisted gastrectomy in the initial clinical application stage.

Surgical endoscopy
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.

Deep learning-based virtual cytokeratin staining of gastric carcinomas to measure tumor-stroma ratio.

Scientific reports
The tumor-stroma ratio (TSR) determined by pathologists is subject to intra- and inter-observer variability. We aimed to develop a computational quantification method of TSR using deep learning-based virtual cytokeratin staining algorithms. Patients ...

Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: White-light endoscopy (WLE) is the most pivotal tool to detect gastric cancer in an early stage. However, the skill among endoscopists varies greatly. Here, we aim to develop a deep learning-based system named ENDOANGEL-LD (lesio...

Robot-assisted Valvuloplastic Esophagogastrostomy by Double-flap Technique Using a Knifeless Linear Stapler After Proximal Gastrectomy.

Surgical laparoscopy, endoscopy & percutaneous techniques
After proximal gastrectomy, valvuloplastic esophagogastrostomy by double-flap technique could be the ideal reconstruction to prevent gastroesophageal reflux. However, it is demanding procedure in laparoscopic surgery. In this video, we demonstrate a ...

Detection of sarcopenic obesity and prediction of long-term survival in patients with gastric cancer using preoperative computed tomography and machine learning.

Journal of surgical oncology
BACKGROUND: Previous studies evaluating the prognostic value of computed tomography (CT)-derived body composition data have included few patients. Thus, we assessed the prevalence and prognostic value of sarcopenic obesity in a large population of ga...

An ensemble learning framework for potential miRNA-disease association prediction with positive-unlabeled data.

Computational biology and chemistry
To explore the pathogenic mechanisms of MicroRNA (miRNA) on diverse diseases, many researchers have concentrated on discovering the potential associations between miRNA and disease using machine learning methods. However, the prediction accuracy of s...

Simultaneous Recognition of Atrophic Gastritis and Intestinal Metaplasia on White Light Endoscopic Images Based on Convolutional Neural Networks: A Multicenter Study.

Clinical and translational gastroenterology
INTRODUCTION: Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic screening and surveillance have been implemented in high incidence countries. The study aimed to evalu...