ArticleInternational journal of molecular sciences2023
Gut Microbes Meet Machine Learning: The Next Step towards Advancing Our Understanding of the Gut Microbiome in Health and Disease.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
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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
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review on Effect of Bifidobacterium Isolated from Skin Microbiota on GLP-1 Production to Alleviate Human Ailments.Probiotics and antimicrobial proteins · 2026Pooled it
- A bibliometric study on the impact of gut microbiota on the efficacy of immune checkpoint inhibitors in cancer patients: analysis of the top 100 cited articles.Frontiers in immunology · 2024Pooled it
- Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling.Gut microbes reports · 2026Review
- Mucosal microbiota signatures reveal diagnostic insights in chronic liver disease.BMC gastroenterology · 2025Article
- Operationalizing Team Science at the Academic Cancer Center Network to Unveil the Structure and Function of the Gut Microbiome.Journal of clinical medicine · 2025Review
- Review
- Delineating the nexus between gut-intratumoral microbiome and osteo-immune system in bone metastases.Bone reports · 2024Review
- AI in microbiome-related healthcare.Microbial biotechnology · 2024Review
- Gut Microbiota Are a Novel Source of Biomarkers for Immunotherapy in Non-Small-Cell Lung Cancer (NSCLC).Cancers · 2024Review
- Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Interwoven processes in fish development: microbial community succession and immune maturation.PeerJ · 2024Review
- Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning.International journal of molecular sciences · 2023Article
- The Gut-Liver-Brain Axis: From the Head to the Feet.International journal of molecular sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human gut microbiome plays a crucial role in human health and has been a focus of increasing research in recent years. Omics-based methods, such as metagenomics, metatranscriptomics, and metabolomics, are commonly used to study the gut microbiome because they provide high-throughput and high-resolution data. The vast amount of data generated by these methods has led to the development of computational methods for data processing and analysis, with machine learning becoming a powerful and widely used tool in this field. Despite the promising results of machine learning-based approaches for analyzing the association between microbiota and disease, there are several unmet challenges. Small sample sizes, disproportionate label distribution, inconsistent experimental protocols, or a lack of access to relevant metadata can all contribute to a lack of reproducibility and translational application into everyday clinical practice. These pitfalls can lead to false models, resulting in misinterpretation biases for microbe-disease correlations. Recent efforts to address these challenges include the construction of human gut microbiota data repositories, improved data transparency guidelines, and more accessible machine learning frameworks; implementation of these efforts has facilitated a shift in the field from observational association studies to experimental causal inference and clinical intervention.
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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.