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Faecal microbiome-based machine learning for multi-class disease diagnosis

Medicine and Health

Faecal microbiome-based machine learning for multi-class disease diagnosis

Q. Su, Q. Liu, et al.

This groundbreaking study by Qi Su and colleagues reveals how the systemic characterization of the human faecal microbiome can lead to innovative, non-invasive disease diagnostics. By leveraging metagenomic data from over 2,300 individuals, the machine-learning model they developed shows impressive predictive power across multiple diseases, showcasing the promise of microbiome-based solutions in clinical applications.

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