AIMC Topic: Microbiota

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The potential value of oral microbial signatures for prediction of oral squamous cell carcinoma based on machine learning algorithms.

Head & neck May 2, 2024
OBJECTIVE: This study aimed to explore the potential predictive value of oral microbial signatures for oral squamous cell carcinoma (OSCC) risk based on machine learning algorithms.
Case-Control Studies Humans Support Vector Machine Machine Learning Female RNA, Ribosomal, 16S Algorithms Adult Carcinoma, Squamous Cell Saliva Dysbiosis Male Aged Microbiota Middle Aged Mouth Predictive Value of Tests Mouth Neoplasms
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Can oral microbiome predict low birth weight infant delivery?

Journal of dentistry Apr 27, 2024
OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning.
Pregnancy Female Infant, Newborn Prospective Studies Biomarkers China RNA, Ribosomal, 16S Saliva Risk Factors Adult Case-Control Studies Humans Machine Learning Infant, Low Birth Weight Microbiota Streptococcus Mouth Leptotrichia
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Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

Frontiers in cellular and infection microbiology Apr 5, 2024
BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, ...
Humans Multiplex Polymerase Chain Reaction Artificial Intelligence ROC Curve Adult Microbiota Support Vector Machine Vaginosis, Bacterial Sensitivity and Specificity Lactobacillus Middle Aged Vagina Female Young Adult
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Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Frontiers in cellular and infection microbiology Apr 3, 2024
Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significantly impair patients' quality of life but also complicate and raise the expense of therapy. It has been discovered in recent years that the pathophysio...
Microbiota Musculoskeletal Diseases Machine Learning Humans Quality of Life Deep Learning
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Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 29, 2024
BACKGROUND: Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or requ...
Metabolome Microbiota Vagina Vaginosis, Bacterial Multiomics RNA, Ribosomal, 16S Metabolomics Humans Young Adult Machine Learning Adult Biomarkers Female
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antibacterial activity of antiretroviral drugs on key commensal bacteria from the human microbiota.

Frontiers in cellular and infection microbiology Jan 8, 2024
INTRODUCTION: Antiretroviral therapy has improved life expectancy in HIV-infected patients. However, people living with HIV under antiretroviral therapy are at higher risks of developing chronic complications and acquiring multidrug resistant bacteri...
Methicillin-Resistant Staphylococcus aureus Microbiota Anti-Retroviral Agents Humans Female Anti-Bacterial Agents HIV Infections Bacteria
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Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology.

mBio Dec 21, 2023
Due to the complex nature of microbiome data, the field of microbial ecology has many current and potential uses for machine learning (ML) modeling. With the increased use of predictive ML models across many disciplines, including microbial ecology, ...
Machine Learning Algorithms Microbiota
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Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics.

Nature communications Dec 1, 2023
The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitative analysis and engineering. By using autoencoder neural networks, we show that microbial growth dynamics can be compressed into low-dimensional repres...
Microbiota Neural Networks, Computer Machine Learning Bacteria
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Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes.

Proceedings of the National Academy of Sciences of the United States of America Nov 22, 2023
Microbiome engineering offers the potential to leverage microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and functio...
Machine Learning Microbiota
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Identifying keystone species in microbial communities using deep learning.

Nature ecology & evolution Nov 16, 2023
Previous studies suggested that microbial communities can harbour keystone species whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an efficient method to systematically identify keystone species in microbial com...
Deep Learning Microbiota Machine Learning
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