The potential value of oral microbial signatures for prediction of oral squamous cell carcinoma based on machine learning algorithms
Baochang He,
Yujie Cao,
Zhaocheng Zhuang
et al.
Abstract:ObjectiveThis study aimed to explore the potential predictive value of oral microbial signatures for oral squamous cell carcinoma (OSCC) risk based on machine learning algorithms.MethodsThe oral microbiome signatures were assessed in the unstimulated saliva samples of 80 OSCC patients and 179 healthy individuals using 16S rRNA gene sequencing. Four different machine learning classifiers were used to develop prediction models.ResultsCompared with control participants, OSCC patients had a higher microbial dysbio… Show more
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