ArticleGenes2019
Using Decision Tree Aggregation with Random Forest Model to Identify Gut Microbes Associated with Colorectal Cancer.
Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 63 citations in OpenAlex.
- Sugar Composition of Thai Desserts and Their Impact on the Gut Microbiome in Healthy Volunteers: A Randomized Controlled Trial.Nutrients · 2024Trial
- Advancements in the study of gut microbiome in disease diagnosis.Antonie van Leeuwenhoek · 2026Review
- Integrating host-microbiome multi-omics with machine learning: methods, benchmarks, and translational applications.Science China. Life sciences · 2026Review
- Transformer Models, Graph Networks, and Generative AI in Gut Microbiome Research: A Narrative Review.Bioengineering (Basel, Switzerland) · 2026Review
- Systems biology and microbiome innovations for personalized diabetic retinopathy management.NPJ systems biology and applications · 2025Review
- Oral microbiome-derived biomarkers for non-invasive diagnosis of head and neck squamous cell carcinoma.NPJ biofilms and microbiomes · 2025Article
- The development of an efficient artificial intelligence-based classification approach for colorectal cancer response to radiochemotherapy: deep learning vs. machine learning.Scientific reports · 2025Article
- Intratumor microbiota and colorectal cancer: Comprehensive and lucid review.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024Article
- Longitudinal Risk Analysis of Second Primary Cancer after Curative Treatment in Patients with Rectal Cancer.Diagnostics (Basel, Switzerland) · 2024Article
- Prediction of Myocardial Infarction Using a Combined Generative Adversarial Network Model and Feature-Enhanced Loss Function.Metabolites · 2024Article
- Cancer invasion and anaerobic bacteria: new insights into mechanisms.Journal of medical microbiology · 2024Review
- Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology.mBio · 2024Review
- Uncovering Predictive Factors and Interventions for Restoring Microecological Diversity after Antibiotic Disturbance.Nutrients · 2023Article
- Leveraging Scheme for Cross-Study Microbiome Machine Learning Prediction and Feature Evaluations.Bioengineering (Basel, Switzerland) · 2023Article
- Identifying microbial signatures for patients with postmenopausal osteoporosis using gut microbiota analyses and feature selection approaches.Frontiers in microbiology · 2023Article
- Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data.Frontiers in microbiology · 2023Article
- Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population.BMC genomics · 2022Article
- Interpreting tree ensemble machine learning models with endoR.PLoS computational biology · 2022Article
- Review of the Current State of Freely Accessible Web Tools for the Analysis of 16S rRNA Sequencing of the Gut Microbiome.International journal of molecular sciences · 2022Review
- The Use of Probiotic Therapy in Metabolic and Neurological Diseases.Frontiers in nutrition · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
The imbalance of human gut microbiota has been associated with colorectal cancer. In recent years, metagenomics research has provided a large amount of scientific data enabling us to study the dedicated roles of gut microbes in the onset and progression of cancer. We removed unrelated and redundant features during feature selection by mutual information. We then trained a random forest classifier on a large metagenomics dataset of colorectal cancer patients and healthy people assembled from published reports and extracted and analysed the information from the learned decision trees. We identified key microbial species associated with colorectal cancers. These microbes included
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.