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Stomach Neoplasms

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Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial.

The lancet. Gastroenterology & hepatology
BACKGROUND: White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during upper gastrointestinal endoscopy due to the subtle nature of these lesions and varying skill among ...

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and diffe...

The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning.

Frontiers in immunology
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies.

Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopic screening is difficult to implement in populous countries. By identifying high-risk individuals fr...

Robotic versus laparoscopic distal gastrectomy in patients with gastric cancer: a propensity score-matched analysis.

BMC surgery
BACKGROUND: Robotic distal gastrectomy (RDG) has been increasingly used for the treatment of gastric cancer (GC). However, whether RDG has a clinical advantage over laparoscopic distal gastrectomy (LDG) is yet to be determined. Thus, this study aimed...

Use of Endoscopic Images in the Prediction of Submucosal Invasion of Gastric Neoplasms: Automated Deep Learning Model Development and Usability Study.

Journal of medical Internet research
BACKGROUND: In a previous study, we examined the use of deep learning models to classify the invasion depth (mucosa-confined versus submucosa-invaded) of gastric neoplasms using endoscopic images. The external test accuracy reached 77.3%. However, mo...

Robotic D2 Total Gastrectomy with Fluorescent Lymphatic Mapping for Gastric Cancer: Effective Use of the 4th Arm.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Minimally invasive surgery techniques have evolved remarkably over the past few decades in the field of surgical oncology, including robotic techniques for gastric malignancies. Bedside surgical assistance is often limited by operating table space or...

Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning.

Nature communications
N-staging is a determining factor for prognostic assessment and decision-making for stage-based cancer therapeutic strategies. Visual inspection of whole-slides of intact lymph nodes is currently the main method used by pathologists to calculate the ...