ArticleFrontiers in microbiology2022
Insights of Host Physiological Parameters and Gut Microbiome of Indian Type 2 Diabetic Patients Visualized
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Investigating the causal association between gut microbiota and type 2 diabetes: a meta-analysis and Mendelian randomization.Frontiers in public health · 2024Pooled it
- Article
- Classifying Diabetic and HealthyComputational and structural biotechnology journal · 2026Article
- Nutrient metabolism and complications of type 2 diabetes mellitus: implications for rehabilitation and precision care.Frontiers in nutrition · 2025Review
- From burden to hope: Noncommunicable diseases in India and the prospects of the gut microbiome.iMetaOmics · 2024Article
- Gut microbial ecology and exposome of a healthy Pakistani cohort.Gut pathogens · 2024Article
- Correlation between gut microbiota composition, enteric infections and linear growth impairment: a case-control study in childhood stunting in Pidie, Aceh, Indonesia.Gut pathogens · 2023Article
- Microbial community structural response to variations in physicochemical features of different aquifers.Frontiers in microbiology · 2023Article
- Sacubitril/Valsartan contributes to improving the diabetic kidney disease and regulating the gut microbiota in mice.Frontiers in endocrinology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Type 2 diabetes (T2D) is a serious public health issue and may also contribute to modification in the structure of the intestinal microbiota, implying a link between T2D and microbial inhabitants in the digestive tract. This work aimed to develop efficient models for identifying essential physiological markers for improved T2D classification using machine learning algorithms. Using amplicon metagenomic approaches, an effort has also been made to understand the alterations in core gut microbial members in Indian T2D patients with respect to their control normal glucose tolerance (NGT). Our data indicate the level of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) were the most useful physiological indicators while random forest and support vector machine with RBF Kernel were effective predictions models for identifications of T2D. The dominating gut microbial members
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Registered trials
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