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Fig. 1 | Journal of Ovarian Research

Fig. 1

From: A metabolic fingerprint of ovarian cancer: a novel diagnostic strategy employing plasma EV-based metabolomics and machine learning algorithms

Fig. 1

Schematic diagram of study approaches and main findings. RF model combined with TSP mass spectrometry analysis of plasma EVs demonstrated a remarkable capability to identify OC patients accurately. Notably, metabolites contributing to this discrimination included hydrazine, maltol, 4-morpholineethanamine, and methyl stearate. These identified metabolites are associated with cancer phenotypes, such as cancer-related mutations, immune responses, and metabolic reprogramming

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