ArticleScientific reports2025
Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Pancreatic Cancer Early Detection Biomarkers for High-Risk Individuals: Insights From the PRECEDE Consortium.International journal of cancer · 2026Review
- Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review.BJC reports · 2026Review
- Machine learning-based multimodal biomarkers enable accurate diagnosis and early detection of pancreatic ductal adenocarcinoma.Scientific reports · 2026Article
- Construction and validation of a multicenter predictive model for neonatal hypoglycemia risk in infants of mothers with gestational diabetes mellitus.American journal of translational research · 2026Article
- Digital intelligence-enabled tumor microbiome research: from mechanistic dissection to clinical translation.Frontiers in oncology · 2026Review
- Fast Fourier transform is a training-free, ultrafast, highly efficient, and fully interpretable approach for epigenomic data compression.Scientific reports · 2025Article
- Unveiling Disparities in Beer Consumer Behavior and Key Drivers Across Regions in China.Foods (Basel, Switzerland) · 2025Article
- Advanced Multipurpose Spectroscopic Nanobio-Device for Concurrent Lab-on-a-Chip Label-Free Separation and Detection of Extracellular Vesicles as Key-Biomarkers for Point-of-Care Cardiovascular Disease Diagnostics.Advanced healthcare materials · 2025Article
- Predictive value of current nodal staging systems and development of machine learning nomogram for resectable pancreatic head cancer: a population-based study and multicenter validation.Frontiers in immunology · 2025Article
- Explainable artificial intelligence in pancreatic cancer prediction: from transparency to clinical decision-making.Frontiers in oncology · 2025Review
- Systemic immune-inflammatory biomarkers combined with the CRP-albumin-lymphocyte index predict surgical site infection following posterior lumbar spinal fusion: a retrospective study using machine learning.Frontiers in medicine · 2025Article
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Authors and funding
10 authors.
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Abstract
Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because of its poor detection rate in early stages. Given emerging evidence of the relationship between microbiota composition and diseases, this study aims to identify microbiome markers linked to the diagnosis of pancreatic cancer. We utilized extracellular vesicles (EVs) data obtained from blood samples of 38 pancreatic cancer patients and 51 health controls. Least absolute shrinkage and selection operator (LASSO) and stepwise method were used to obtain some candidate markers in genus and phylum levels. These markers were used to develop various machine learning models including logistic regression (LR), random forest (RF), support vector machine (SVM), and Deep Neural Network (DNN) methods. In phylum level, DNN performed best with three markers (Verrucomicrobia, Actinobacteria and Proteobacteria) selected by stepwise method with the test AUC 0.959. In genus level, DNN using 11 markers selected by LASSO (Ruminococcaceae UCG-013, Ruminiclostridium, Propionibacterium, Lachnospiraceae NK4A136 group, Corynebacterium.1, Akkermansia, Mucispirillum, Pseudomonas, Diaphorobacter, Clostridium sensu stricto 1 and Turicibacter) outperformed others with 0.961 test AUCs. These results highlight the potential of microbiome markers and prediction models in clinical studies of PC diagnosis.
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