AIMC Topic: Stomach Neoplasms
Clear Filters Showing 71 to 80 of 439 articles
Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 3, 2024
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...
AutoLNMNet: Automated Network for Estimating Lymph-Node Metastasis in EGC Using a Pyramid Vision Transformer and Data Derived From Multiphoton Microscopy.
Microscopy research and technique
Oct 1, 2024
Lymph-node status is important in decision-making during early gastric cancer (EGC) treatment. Currently, endoscopic submucosal dissection is the mainstream treatment for EGC. However, it is challenging for even experienced endoscopists to accurately...
Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics.
Molecular and cellular probes
Sep 30, 2024
AIM: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics.
Raman fiber-optic probe for rapid diagnosis of gastric and esophageal tumors with machine learning analysis or similarity assessments: a comparative study.
Analytical and bioanalytical chemistry
Sep 25, 2024
Gastric and esophageal cancers, the predominant forms of upper gastrointestinal malignancies, contribute significantly to global cancer mortality. Routine detection methods, including medical imaging, endoscopic examination, and pathological biopsy, ...
Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.
Frontiers in immunology
Sep 19, 2024
BACKGROUND: Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects patient prognosis. Using large-scale datasets and machine learning algorithms for prediction can improv...
Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.
Scientific reports
Sep 18, 2024
Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD) is a unique form of programmed cell death that is closely linked to antitumor immunity and plays a critical role in modulating the tumor microenviro...
Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Sep 14, 2024
BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clinic. The collagen alterations in tumor microenvironment affect the migration and treatment response of cancer cells. Herein, we proposed multitask machi...
A Machine Learning-Driven Surface-Enhanced Raman Scattering Analysis Platform for the Label-Free Detection and Identification of Gastric Lesions.
International journal of nanomedicine
Sep 10, 2024
BACKGROUND: Gastric lesions pose significant clinical challenges due to their varying degrees of malignancy and difficulty in early diagnosis. Early and accurate detection of these lesions is crucial for effective treatment and improved patient outco...
An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.
Academic radiology
Aug 30, 2024
RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of pa...
Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.
Medical physics
Aug 17, 2024
BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable f...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31032
- Neural Networks, Computer 29717
- Algorithms 26831
- Deep Learning 26345
- Artificial Intelligence 24290
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9110
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4770
- Support Vector Machine 4686
- Computational Biology 4236
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5940
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2929
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1854
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 943
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826