Endometrial cancer (EC) diagnostic suffers from a lack of non-invasive, specific and sensitive tools. Machine learning of high-performance serum metabolic fingerprints (SMFs) was used to identify a metabolic biomarker panel for differentiation diagnosis of EC vs. Non-EC.
All Keywords
【저자키워드】 mass spectrometry, Biomarker, Biomarkers, machine learning, Cancer, metabolite, Endometrial Cancer, Urogenital system,
【저자키워드】 mass spectrometry, Biomarker, Biomarkers, machine learning, Cancer, metabolite, Endometrial Cancer, Urogenital system,