AIMC Topic: Stomach Neoplasms
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Development and validation of CT-based fusion model for preoperative prediction of invasion and lymph node metastasis in adenocarcinoma of esophagogastric junction.
BMC medical imaging
Jul 1, 2025
PURPOSE: In the context of precision medicine, radiomics has become a key technology in solving medical problems. For adenocarcinoma of esophagogastric junction (AEG), developing a preoperative CT-based prediction model for AEG invasion and lymph nod...
Muscle-Driven prognostication in gastric cancer: A multicenter deep learning framework integrating Iliopsoas and erector spinae radiomics for 5-Year survival prediction.
Scientific reports
Jul 1, 2025
This study developed a 5-year survival prediction model for gastric cancer patients by combining radiomics and deep learning, focusing on CT-based 2D and 3D features of the iliopsoas and erector spinae muscles. Retrospective data from 705 patients ac...
A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images.
Biomedical engineering online
Jun 25, 2025
OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for classifying gastric adenocarcinoma differentiation on whole-slide images (WSIs) without manual annotation...
Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with "double invasion" for personalized patient care.
European journal of medical research
Jun 23, 2025
OBJECTIVE: To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion.
Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.
Analytical chemistry
Jun 11, 2025
Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current clinical diagnosis relies on endoscopic biopsy and histopathological analysis, which are highly depende...
Interpretable deep learning for gastric cancer detection: a fusion of AI architectures and explainability analysis.
Frontiers in immunology
May 29, 2025
INTRODUCTION: The rise in cases of Gastric Cancer has increased in recent times and demands accurate and timely detection to improve patients' well-being. The traditional cancer detection techniques face issues of explainability and precision posing ...
Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.
Nature communications
May 22, 2025
In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography w...
Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease.
Journal of translational medicine
May 16, 2025
INTRODUCTION: Gastrointestinal disorders (GIDs) affect nearly 40% of the global population, with gut microbiome-metabolome interactions playing a crucial role in gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD). This...
Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study.
Gut
May 7, 2025
BACKGROUND AND OBJECTIVE: Gastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome non-coding RNAs (ncRNAs), a type of liquid biopsy, have emerged as promising diagnostic biomarkers f...
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.
BMC cancer
May 6, 2025
BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatment strategies. This study aimed to integrate radiomic features and clinical biomarkers through machin...
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