Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination.

Takeshi MurataTakako YanagisawaToshiaki KuriharaMiku KanekoSana OtaAyame EnomotoMasaru TomitaMasahiro SugimotoMakoto SunamuraTetsu HayashidaYuko KitagawaHiromitsu Jinno

Published in: Breast cancer research and treatment (2019)

These data indicated that combinations of salivary metabolomics with the ADTree-based machine learning methods show potential for non-invasive screening of breast cancer.

Keyphrases

machine learning
big data
mass spectrometry
artificial intelligence
electronic health record
deep learning
decision making
breast cancer risk
risk assessment