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. 2020 Jun;9(3):693–704. doi: 10.21037/tlcr-19-590

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2020 Translational Lung Cancer Research. All rights reserved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0.

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The random forest model based on the microbiota and tumor markers (TMs) to distinguish lung cancer and benign pulmonary diseases patients. (A) Receiver operating characteristic (ROC) curves with the ten significant differential genera (AUC =79.12%), three tumor markers for lung cancer (AUC =78.27%) and combination of these genera and clinical tumor markers (AUC =84.52%) to predict lung cancer versus benign pulmonary diseases; (B) the importance of Gini coefficient was arranged from top to bottom.