AI Article Synopsis
- Machine learning is becoming crucial in microbiology for predicting antibiotic resistance and linking microbiome features to diseases.
- The applications of machine learning in this field are growing and include techniques like classification, regression, clustering, and dimensionality reduction.
- This review outlines key machine learning concepts and tools, equipping microbiologists with the knowledge to understand and apply these techniques in their research.
Article Abstract
Machine learning is increasingly important in microbiology where it is used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex host diseases. The applications in microbiology are quickly expanding and the machine learning tools frequently used in basic and clinical research range from classification and regression to clustering and dimensionality reduction. In this Review, we examine the main machine learning concepts, tasks and applications that are relevant for experimental and clinical microbiologists. We provide the minimal toolbox for a microbiologist to be able to understand, interpret and use machine learning in their experimental and translational activities.
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| http://dx.doi.org/10.1038/s41579-023-00984-1 | DOI Listing |
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