AIMC Topic: Stomach Neoplasms

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Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer.

BMC public health
BACKGROUND: Deep learning (DL), a specialized form of machine learning (ML), is valuable for forecasting survival in various diseases. Its clinical applicability in real-world patients with gastric cancer (GC) has yet to be extensively validated.

Da Vinci robot-assisted endoscopic full-thickness gastric resection with regional lymph node dissection using a 3D near-infrared video system: a single-center 5-year clinical outcome.

Surgical endoscopy
BACKGROUND: Endoscopic full-thickness gastric resection (EFTGR) with regional lymph node dissection (LND) has been used for early gastric cancer (EGC) exceeding the indications for endoscopic submucosal dissection (ESD). The extent of the dissected l...

The effect of incorporating domain knowledge with deep learning in identifying benign and malignant gastric whitish lesions: A retrospective study.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Early whitish gastric neoplasms can be easily misdiagnosed; differential diagnosis of gastric whitish lesions remains a challenge. We aim to build a deep learning (DL) model to diagnose whitish gastric neoplasms and explore the ef...

A deep learning model based on magnifying endoscopy with narrow-band imaging to evaluate intestinal metaplasia grading and OLGIM staging: A multicenter study.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND AND PURPOSE: Patients with stage III or IV of operative link for gastric intestinal metaplasia assessment (OLGIM) are at a higher risk of gastric cancer (GC). We aimed to construct a deep learning (DL) model based on magnifying endoscopy w...

First clinical experiences of robotic gastrectomy for gastric cancer using the hinotori™ surgical robot system.

Surgical endoscopy
BACKGROUND: Although the da Vinci™ Surgical System is the most predominantly used surgical robot worldwide, other surgical robots are being developed. The Japanese surgical robot hinotori™ Surgical Robot System was launched and approved for clinical ...

Predicting malnutrition in gastric cancer patients using computed tomography(CT) deep learning features and clinical data.

Clinical nutrition (Edinburgh, Scotland)
OBJECTIVE: The aim of this study is using clinical factors and non-enhanced computed tomography (CT) deep features of the psoas muscles at third lumbar vertebral (L3) level to construct a model to predict malnutrition in gastric cancer before surgery...

An artificial intelligence system for chronic atrophic gastritis diagnosis and risk stratification under white light endoscopy.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND AND AIMS: The diagnosis and stratification of gastric atrophy (GA) predict patients' gastric cancer progression risk and determine endoscopy surveillance interval. We aimed to construct an artificial intelligence (AI) system for GA endosco...

Diagnostic performance of deep-learning-based virtual chromoendoscopy in gastric neoplasms.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUNDS: Cycle-consistent generative adversarial network (CycleGAN) is a deep neural network model that performs image-to-image translations. We generated virtual indigo carmine (IC) chromoendoscopy images of gastric neoplasms using CycleGAN and ...