AIMC Topic: Gastrointestinal Microbiome

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Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.

Gut microbes Jan 1, 2022
The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this stu...
Humans Machine Learning Bacteria Gastrointestinal Microbiome Metagenomics Aging Cohort Studies Biomarkers
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Artificial intelligence and metagenomics in intestinal diseases.

Journal of gastroenterology and hepatology Apr 1, 2021
Gut microbiota has been shown to associate with the development of gastrointestinal diseases. In the last decade, development in whole metagenome sequencing and 16S rRNA sequencing technology has dramatically accelerated the gut microbiome's research...
Machine Learning Sequence Analysis, RNA Gastrointestinal Microbiome Humans Artificial Intelligence Gastrointestinal Diseases RNA, Ribosomal, 16S Metagenomics
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Applying artificial intelligence in the microbiome for gastrointestinal diseases: A review.

Journal of gastroenterology and hepatology Apr 1, 2021
For a long time, gut bacteria have been recognized for their important roles in the occurrence and progression of gastrointestinal diseases like colorectal cancer, and the ever-increasing amounts of microbiome data combined with other high-quality cl...
Artificial Intelligence Big Data Information Storage and Retrieval Gastrointestinal Diseases Gastrointestinal Microbiome Datasets as Topic
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Machine learning on microbiome research in gastrointestinal cancer.

Journal of gastroenterology and hepatology Apr 1, 2021
Gastrointestinal cancer maintains the highest incidence and mortality rate among all cancers globally. In addition to genetic causes, it has been reported that individuals' diet and composition of the gastrointestinal microbiome have profound impacts...
High-Throughput Nucleotide Sequencing Gastrointestinal Microbiome Gastrointestinal Neoplasms Artificial Intelligence Machine Learning Humans Research Deep Learning Research Design
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Gut Microbiota in T1DM-Onset Pediatric Patients: Machine-Learning Algorithms to Classify Microorganisms as Disease Linked.

The Journal of clinical endocrinology and metabolism Sep 1, 2020
AIMS: The purpose of this work is to find the gut microbial fingerprinting of pediatric patients with type 1 diabetes.
Feces Diabetes Mellitus, Type 1 Age of Onset Metagenome Gastrointestinal Microbiome Cohort Studies Child, Preschool Child Male Adolescent Humans Machine Learning Female Algorithms Risk Factors
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mAML: an automated machine learning pipeline with a microbiome repository for human disease classification.

Database : the journal of biological databases and curation Jan 1, 2020
Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems aiming to get rid of the tediousness in manually performing ML tasks are in great demand. Here we d...
Humans Machine Learning Computational Biology Software Gastrointestinal Microbiome Databases, Factual Disease
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[A machine learning model based on initial gut microbiome data for predicting changes of Bifidobacterium after prebiotics consumption].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Mar 20, 2018
OBJECTIVE: To investigate the effects of prebiotics supplementation for 9 days on gut microbiota structure and function and establish a machine learning model based on the initial gut microbiota data for predicting the variation of Bifidobacterium af...
Feces Gastrointestinal Microbiome RNA, Ribosomal, 16S Humans Double-Blind Method Bifidobacterium Machine Learning Prebiotics
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AI Tackles Hospital Infections: Machine Learning Is Helping Clinicians.

IEEE pulse Jan 1, 2018
For Ashley Zappia (Figure 1), getting her hands dirty was part of her job. Even though she always tried to remain as clean as possible, her work as a nursing aide at a Southern California hospital required a lot of diapering, changing, and other hand...
Cross Infection Humans Clostridium Infections Machine Learning Gastrointestinal Microbiome Risk Factors Immunocompromised Host Clostridioides difficile Infection Control Medical Informatics
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[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Mar 20, 2017
OBJECTIVE: To establish a machine learning model based on gut microbiota for predicting the level of trimethylamine N-oxide (TMAO) metabolism in vivo after choline intake to provide guidance of individualized precision diet and evidence for screening...
Oxides Algorithms Humans Eggs Gastrointestinal Microbiome Choline Machine Learning Healthy Volunteers RNA, Ribosomal, 16S Methylamines
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