ArticleFrontiers in cellular and infection microbiology2024
Application of tongue image characteristics and oral-gut microbiota in predicting pre-diabetes and type 2 diabetes with machine learning.
Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Artificial Intelligence Meets Oral Medicine: Extending the Capabilities of Human Intelligence.International dental journal · 2026Review
- Oral Microbiota and Type 2 Diabetes: Interactions, Potential Mechanisms, and Preventive Strategies.Microorganisms · 2026Review
- [Recent Research Progress and Prospects on Periodontitis Affecting Systemic Comorbidities via the Oral-Gut Axis].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Review
- Temperature and humidity-dependent interaction effects on tongue color in diabetic patients: a quantitative analysis and TCM perspective.Frontiers in endocrinology · 2026Article
- Integrated multi-omics analysis unveils microbiota-metabolite-host interactions and novel biomarkers for early diabetic kidney disease diagnosis.Frontiers in immunology · 2026Article
- Development of a cold-heat syndrome classification model for children with allergic rhinitis based on multimodal data.Translational pediatrics · 2025Article
- Comparable tongue coating microbiota profiles from a simplified single-swab versus different sampling approaches: A pilot study.Clinical oral investigations · 2025Article
- Article
- A Systemic Perspective of the Link Between Microbiota and Cardiac Health: A Literature Review.Life (Basel, Switzerland) · 2025Review
- Applications of Artificial Intelligence and Machine Learning in Prediabetes: A Scoping Review.Journal of diabetes science and technology · 2025Review
- Clinical study of intelligent tongue diagnosis and oral microbiome for classifying TCM syndromes in MASLD.Chinese medicine · 2025Article
- Characteristics of tongue images and tongue coating bacteria in patients with colorectal cancer.BMC microbiology · 2025Article
- Artificial Intelligence in Oral Diagnosis: Detecting Coated Tongue with Convolutional Neural Networks.Diagnostics (Basel, Switzerland) · 2025Article
- Deep learning approach for objective differentiation of kidney deficiency syndrome in reproductive age females: a tongue-face fusion model.Frontiers in physiology · 2025Article
- ThickFrontiers in cellular and infection microbiology · 2025Article
- Intelligent tongue and facial image analysis for noninvasive prediction of glucolipid metabolic disorders.Digital healthArticle
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to characterize the oral and gut microbiota in prediabetes mellitus (Pre-DM) and type 2 diabetes mellitus (T2DM) patients while exploring the association between tongue manifestations and the oral-gut microbiota axis in diabetes progression. Methods: Participants included 30 Pre-DM patients, 37 individuals with T2DM, and 28 healthy controls. Tongue images and oral/fecal samples were analyzed using image processing and 16S rRNA sequencing. Machine learning techniques, including support vector machine (SVM), random forest, gradient boosting, adaptive boosting, and K-nearest neighbors, were applied to integrate tongue image data with microbiota profiles to construct predictive models for Pre-DM and T2DM classification. Results: Significant shifts in tongue characteristics were identified during the progression from Pre-DM to T2DM. Elevated Firmicutes levels along the oral-gut axis were associated with white greasy fur, indicative of underlying metabolic changes. An SVM-based predictive model demonstrated an accuracy of 78.9%, with an AUC of 86.9%. Notably, tongue image parameters (TB-a, perALL) and specific microbiota ( Conclusion: The integration of tongue diagnosis with microbiome analysis reveals distinct tongue features and microbial markers. This approach significantly improves the diagnostic capability for Pre-DM and T2DM.
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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 Socratic graph.