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Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy.

Shih-Chun ChengKueian ChenChih-Yung ChiuKuan-Ying LuHsin-Ying LuMeng-Han ChiangCheng-Kun TsaiChi-Jen LoMei-Ling ChengTing-Chang ChangGigin Lin
Published in: Metabolomics : Official journal of the Metabolomic Society (2019)
Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.
Keyphrases
  • endometrial cancer
  • machine learning
  • deep learning
  • loop mediated isothermal amplification
  • label free