AIMC Topic: Stomach Neoplasms

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Prediction of Epstein-Barr Virus Status in Gastric Cancer Biopsy Specimens Using a Deep Learning Algorithm.

JAMA network open
IMPORTANCE: Epstein-Barr virus (EBV)-associated gastric cancer (EBV-GC) is 1 of 4 molecular subtypes of GC and is confirmed by an expensive molecular test, EBV-encoded small RNA in situ hybridization. EBV-GC has 2 histologic characteristics, lymphoid...

Robotic radical distal gastrectomy for gastric cancer using the soft coagulation scissors technique.

Journal of robotic surgery
We have developed a novel technique for safe and precise lymph-node dissection during robotic gastrectomy for gastric cancer using monopolar curved scissors with soft coagulation. This technique is called the soft coagulation scissors technique. The ...

Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND AND STUDY AIMS: The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) classifier for differentiating intramucosal and submucosal gastric can...

Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer.

International journal of cancer
Microsatellite instability (MSI) status is an important prognostic marker for various cancers. Furthermore, because immune checkpoint inhibitors are much more effective in tumors with high level of MSI (MSI-H), MSI status is routinely tested in multi...

Impact of Hospital Volume on Utilization of Minimally Invasive Surgery for Gastric Cancer.

The American surgeon
BACKGROUND: Minimally invasive surgery (MIS) for gastric cancer is increasingly performed. The purpose of this study is to evaluate trends in utilization of laparoscopic and robotic techniques compared to open surgery as well as utilization based on ...

Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate pre-treatment prediction of neoadjuvant chemotherapy (NACT) resistance in patients with locally advanced gastric cancer (LAGC) is essential for timely surgeries and optimized treatments. We aim to evaluate the effectiveness of de...

Computed Tomography-Based Deep Learning Nomogram Can Accurately Predict Lymph Node Metastasis in Gastric Cancer.

Digestive diseases and sciences
BACKGROUND: Computed tomography is the most commonly used imaging modality for preoperative assessment of lymph node status, but the reported accuracy is unsatisfactory.

The Use of Deep Learning-Based Computer Diagnostic Algorithm for Detection of Lymph Node Metastases of Gastric Adenocarcinoma.

International journal of surgical pathology
The diversifying modalities of treatment for gastric cancer raise urgent demands for the rapid and precise diagnosis of metastases in regional lymph nodes, thereby significantly impact the workload of pathologists. Meanwhile, the recent advent of wh...

Artificial intelligence for diagnosing gastric lesions under white-light endoscopy.

Surgical endoscopy
BACKGROUND: The ability of endoscopists to identify gastric lesions is uneven. Even experienced endoscopists may miss or misdiagnose lesions due to heavy workload or fatigue or subtle changes in lesions under white-light endoscopy (WLE). This study a...

Deep learning as a novel method for endoscopic diagnosis of chronic atrophic gastritis: a prospective nested case-control study.

BMC gastroenterology
BACKGROUND AND AIMS: Chronic atrophic gastritis (CAG) is a precancerous disease that often leads to the development of gastric cancer (GC) and is positively correlated with GC morbidity. However, the sensitivity of the endoscopic diagnosis of CAG is ...