AIMC Topic: Stomach Neoplasms
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Exploring the potential of machine learning in gastric cancer: prognostic biomarkers, subtyping, and stratification.
BMC cancer
Apr 30, 2025
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most impo...
Artificial neural network model enhancing the accuracy of clinical evaluation for high-risk population of lymph node metastasis in non-intestinal type early gastric cancer: a multicenter real-world study in China.
International journal of surgery (London, England)
Apr 18, 2025
BACKGROUND: Recent years have witnessed a proliferation of studies aimed at developing clinical models capable of predicting lymph node metastasis (LNM) in early gastric cancer (EGC), yet tools for prediction grounded in the Lauren classification rem...
An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images.
Scientific reports
Apr 16, 2025
The importance of gastric cancer (GC) and the role of deep learning techniques in categorizing GC histopathology images have recently increased. Identifying the drawbacks of traditional deep learning models, including lack of interpretability, inabil...
Development and application of deep learning-based diagnostics for pathologic diagnosis of gastric endoscopic submucosal dissection specimens.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Apr 15, 2025
BACKGROUND: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identifying tumor areas in serially sectioned ESD specimens requires experience and is time-consuming. This study aimed to develop and evaluate a deep learn...
Transformer-based skeletal muscle deep-learning model for survival prediction in gastric cancer patients after curative resection.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Apr 15, 2025
BACKGROUND: We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal muscle computed tomography (CT) imaging to predict the survival of patients with gastric cancer (GC).
Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.
Scientific reports
Apr 14, 2025
The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer patients has gained significant attention in recent research. Sarcopenia, characterized by the progress...
A machine learning approach to risk-stratification of gastric cancer based on tumour-infiltrating immune cell profiles.
Annals of medicine
Apr 10, 2025
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease, and the response of patients to clinical treatment varies substantially. There is no satisfactory strategy for predicting curative effects to date. We aimed to explore a new method fo...
An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.
BMC gastroenterology
Apr 9, 2025
BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtypes of gastric submucosal tumors (SMTs) characterized by distinct biological characteristics and treatment modalities. The accurate differentiation betw...
Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.
BMC cancer
Apr 9, 2025
BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely complex biological characteristics. Lysine and its metabolism are closely related to human cancer, but little is known about how lysine metabolism-related ...
Single-Cell Gene Expression Analysis
Computational Biology
Sequence Analysis, RNA
Gene Expression Regulation, Neoplastic
Cell Line, Tumor
Single-Cell Analysis
RNA-Seq
Gene Regulatory Networks
Lysine
Nomograms
Cell Proliferation
Carcinogenesis
Vimentin
Humans
Machine Learning
Prognosis
Stomach Neoplasms
Biomarkers, Tumor
T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging.
Frontiers in immunology
Apr 8, 2025
BACKGROUND: T-cell receptor (TCR) repertoires provide insights into tumor immunology, yet their variations across digestive system cancers are not well understood. Characterizing TCR differences between colorectal cancer (CRC) and gastric cancer (GC)...
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