ArticleJournal of oral microbiology2025
An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer.
Article in Journal of oral microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Decoding the cancer microbiome: multi-omics, AI, and translational opportunities.Genome biology · 2026Review
- Alterations in gut microbiota and metabolic profiling are associated with papillary thyroid cancer and BRAFEndocrine · 2026Article
- The Oral-Gastric Microbial Axis in Gastric Cancer: Mechanisms Underlying Development and Progression.Cancers · 2026Review
- Characterization of the Oral and Stomach Microbial Community Structure in Patients with Intestinal Metaplasia, Dysplasia, and Gastric Cancer Through High-Throughput Sequencing.Microorganisms · 2026Article
- Integrated microbial and transcriptomic profiling reveals distinct correlations in atrophic gastritis associated with liver cirrhosis.Frontiers in cellular and infection microbiology · 2026Article
- From Tumor Biology to Clinical Perspectives: Novel Biomarkers and Therapeutic Insights in Gastric Cancer.Oncology research · 2026Review
- WHFDL: an explainable method based on World Hyper-heuristic and Fuzzy Deep Learning approaches for gastric cancer detection using metabolomics data.BioData mining · 2025Article
- A review on computer-aided diagnostic system to classify the disorders of the gastrointestinal tract.European journal of medical research · 2025Review
- Unveiling the microbial influence: bacteria's dual role in tumor metastasis.Frontiers in oncology · 2025Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aims to develop an oral microbiota-based model for gastric cancer (GC) risk stratification and prognosis prediction. Methods: Oral microbial markers for GC prognosis and risk stratification were identified from 99 GC patients, and their predictive potential was validated on an external dataset of 111 GC patients. The identified bacterial markers were used to construct a Deep Neural Network (DNN) model, a Random Forest (RF) model, and a Support Vector Machine (SVM) model for predicting GC prognosis. Results: GC patients with <3 years of survival showed a higher abundance of Conclusion: The oral microbiota-based DNN model may advance GC prognosis. The biological functions of these oral bacterial markers warrant further investigation from the perspective of GC progression.
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