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Stomach Neoplasms

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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 ...

Comparison of Short-Term Outcomes After Robotic Versus Laparoscopic Radical Gastrectomy for Advanced Gastric Cancer in Elderly Individuals: A Propensity Score-Matching Study.

Annals of surgical oncology
BACKGROUND: Robotic gastrectomy (RG) has been widely used to treat gastric cancer. However, whether the short-term outcomes of robotic gastrectomy are superior to those of laparoscopic gastrectomy (LG) for elderly patients with advanced gastric cance...

The effect of thalidomide on the invasive ability of gastric cancer cells by regulating miR-524-5p/FSTL1.

Cellular and molecular biology (Noisy-le-Grand, France)
This study aimed to investigate the effect of thalidomide (Thal) regulating microRNA (miR)-524-5p/follistatin-like protein 1 (FSTL1) on the invasion ability of gastric cancer cells. For this purpose, real-time fluorescent quantitative PCR (RT-qPCR) w...

Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
OBJECTIVE: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We aimed to establish and validate a diagnostic approach for gastric biopsy specimens using deep learn...

Diagnostic accuracy of radiomics-based machine learning for neoadjuvant chemotherapy response and survival prediction in gastric cancer patients: A systematic review and meta-analysis.

European journal of radiology
BACKGROUND: In recent years, researchers have explored the use of radiomics to predict neoadjuvant chemotherapy outcomes in gastric cancer (GC). Yet, a lingering debate persists regarding the accuracy of these predictions. Against this backdrop, this...

Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

Annals of surgical oncology
BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant c...