ReviewFrontiers in medical technology2024
Advanced computational tools, artificial intelligence and machine-learning approaches in gut microbiota and biomarker identification.
Review in Frontiers in medical technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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
23 citing papers in PubMed.
- The Role of Artificial Intelligence and Machine Learning in Revolutionizing Probiotic Research.Microorganisms · 2026Review
- Role of epithelial-mesenchymal transition (EMT) in malignancies: current status and future prospects.Signal transduction and targeted therapy · 2026Review
- Targeting the Gut-Heart Axis in Atherosclerosis: Microbial Metabolites, Molecular Mechanisms, and Precision Therapeutics.Probiotics and antimicrobial proteins · 2026Review
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- The Gut-Liver Axis in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): Mechanisms, Microbiome Interactions and Therapeutic Targets.Probiotics and antimicrobial proteins · 2026Review
- Host-Microbiota Metabolic Interactions in Atherosclerosis: Oral, gut, and Blood Perspectives.Probiotics and antimicrobial proteins · 2026Review
- Exploring the oral microbiome: from traditional techniques to advanced omics and databases.Antonie van Leeuwenhoek · 2026Review
- Urinary Microbiome Characteristics in Kidney Transplant Recipients and Their Clinical Implications: A Narrative Review.Annals of transplantation · 2026Review
- Emerging Therapeutic Approaches for Modulating the Intestinal Microbiota.Pharmaceutics · 2026Review
- Artificial intelligence in functional food innovation: Bioactive enhancement and formulation optimization: A quasi-systematic review.Food chemistry: X · 2026Review
- The impact of gut microbiota on cervical cancer and precancerous lesions: neglected status, mechanisms, challenges, and a call to action.Frontiers in immunology · 2026Review
- The role of the gut-lung axis in persistent inflammation and disease progression in chronic obstructive pulmonary disease: mechanistic evidence and therapeutic implications.Frontiers in immunology · 2026Review
- From dysbiosis to malignancy: decoding gut-driven pathways to clinical management in hepatocellular carcinoma.Frontiers in cellular and infection microbiology · 2026Review
- Arbuscular Mycorrhizal Fungi as Core Engineers in Synthetic Microbial Communities: Boosting Plant Growth and Soil Health for Sustainable Agriculture.Journal of fungi (Basel, Switzerland) · 2025Review
- From AI-AssistedPharmaceuticals (Basel, Switzerland) · 2025Review
- Research Advances of Extrachromosomal Circular DNA in Breast Cancer.Cancer medicine · 2025Review
- MASLD Under the Microscope: How microRNAs and Microbiota Shape Hepatic Metabolic Disease Progression.International journal of molecular sciences · 2025Review
- Skin in the game: a review of computational models of the skin.BioData mining · 2025Review
- Sustainable Innovations in Food Microbiology: Fermentation, Biocontrol, and Functional Foods.Foods (Basel, Switzerland) · 2025Review
- Gut bioengineered models to study host-microbiota-probiotics interactions.Microbiome research reports · 2025Article
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 microbiome of the gut is a complex ecosystem that contains a wide variety of microbial species and functional capabilities. The microbiome has a significant impact on health and disease by affecting endocrinology, physiology, and neurology. It can change the progression of certain diseases and enhance treatment responses and tolerance. The gut microbiota plays a pivotal role in human health, influencing a wide range of physiological processes. Recent advances in computational tools and artificial intelligence (AI) have revolutionized the study of gut microbiota, enabling the identification of biomarkers that are critical for diagnosing and treating various diseases. This review hunts through the cutting-edge computational methodologies that integrate multi-omics data-such as metagenomics, metaproteomics, and metabolomics-providing a comprehensive understanding of the gut microbiome's composition and function. Additionally, machine learning (ML) approaches, including deep learning and network-based methods, are explored for their ability to uncover complex patterns within microbiome data, offering unprecedented insights into microbial interactions and their link to host health. By highlighting the synergy between traditional bioinformatics tools and advanced AI techniques, this review underscores the potential of these approaches in enhancing biomarker discovery and developing personalized therapeutic strategies. The convergence of computational advancements and microbiome research marks a significant step forward in precision medicine, paving the way for novel diagnostics and treatments tailored to individual microbiome profiles. Investigators have the ability to discover connections between the composition of microorganisms, the expression of genes, and the profiles of metabolites. Individual reactions to medicines that target gut microbes can be predicted by models driven by artificial intelligence. It is possible to obtain personalized and precision medicine by first gaining an understanding of the impact that the gut microbiota has on the development of disease. The application of machine learning allows for the customization of treatments to the specific microbial environment of an individual.
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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 OpenQuestion graph.