AI tool finds biological signals in the gut microbiome that other methods miss, may flag early signs of disease
University of Missouri researchers are using artificial intelligence to uncover hidden clues among the trillions of bacteria living in the human gut, including changes that could one day help scientists detect diseases earlier. The Mizzou team—which brings together expertise in medicine, data science and engineering—developed a new machine-learning tool capable of finding biological signals that…
Researchers at the University of Missouri have developed a novel artificial intelligence tool to uncover subtle biological signals in the human gut microbiome. The tool, called Metric Learning for Statistical Inference (MeLSI), can identify changes in the trillions of bacteria residing in the gut that conventional methods often overlook.
Published in the journal mSystems, the study led by Ai-Ling Lin and Nathan Bresette demonstrates how MeLSI can reveal specific microbes responsible for key biological changes that may precede symptoms of diseases like Alzheimer's by months or even years. By focusing on the most relevant aspects of microbiome data, MeLSI provides researchers with a more precise understanding of the microbiome's role in health and disease, potentially enabling earlier interventions.
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