Supervised machine learning-based classification of oral malodor based on the microbiota in saliva samples

Conclusions: Using T-RF proportions and frequencies, models to classify the presence of methyl mercaptan, a volatile sulfur-containing compound that causes oral malodor, were developed. SVM classifiers successfully classified the presence of methyl mercaptan with high specificity, and this classification is expected to be useful for screening saliva for oral malodor before visits to specialist clinics. Classification by a SVM and an ANN does not require the identification of the oral microbiota species responsible for the malodor, and the ANN also does not require the proportions of T-RFs.

Source: Artificial Intelligence in Medicine - January 16, 2014 Category: Bioinformatics Authors: Yoshio Nakano, Toru Takeshita, Noriaki Kamio, Susumu Shiota, Yukie Shibata, Nao Suzuki, Masahiro Yoneda, Takao Hirofuji, Yoshihisa Yamashita Tags: Research Articles Source Type: research