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Stomach Neoplasms

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Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology.

Seminars in cancer biology
Gastric cancer is a leading contributor to cancer incidence and mortality globally. Recently, artificial intelligence approaches, particularly machine learning and deep learning, are rapidly reshaping the full spectrum of clinical management for gast...

Diagnosis of gastric cancer based on hybrid genes selection approach.

Biotechnology & genetic engineering reviews
Gastric cancer (GC) is the third leading cause of cancer death worldwide. In the field of medicine, machine learning is widely used in genetic data mining and the construction of diagnostic models. This study proposed an intelligent model DERFS-XGBoo...

Robotic gastrectomy for gastric cancer: systematic review and future directions.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Robotic gastrectomy (RG) using the da Vinci Surgical System for gastric cancer was approved for national medical insurance coverage in Japan in April 2018, and its number has been rapidly increasing since then.

Robotic versus open approach in total gastrectomy for gastric cancer: a comparative single-center study of perioperative outcomes.

Journal of robotic surgery
The robotic approach to gastric cancer has been gaining interest in recent years; however, its benefit over the open procedure in total gastrectomy with D2 lymphadenectomy is still controversial. The aims of the study were to compare postoperative mo...

Requirement of image standardization for AI-based macroscopic diagnosis for surgical specimens of gastric cancer.

Journal of cancer research and clinical oncology
PURPOSE: The pathological diagnosis of surgically resected gastric cancer involves both a macroscopic diagnosis by gross observation and a microscopic diagnosis by microscopy. Macroscopic diagnosis determines the location and stage of the disease and...

Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study.

Endoscopy
BACKGROUND : Deep learning models have previously been established to predict the histopathology and invasion depth of gastric lesions using endoscopic images. This study aimed to establish and validate a deep learning-based clinical decision support...

Early gastric cancer segmentation in gastroscopic images using a co-spatial attention and channel attention based triple-branch ResUnet.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The artificial segmentation of early gastric cancer (EGC) lesions in gastroscopic images remains a challenging task due to reasons including the diversity of mucosal features, irregular edges of EGC lesions and nuances betwe...

A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video).

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: White light (WL) and weak-magnifying (WM) endoscopy are both important methods for diagnosing gastric neoplasms. This study constructed a deep-learning system named ENDOANGEL-MM (multi-modal) aimed at real-time diagnosing gastric neoplasm...