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. 2023 Feb 2;6(1):pbad001. doi: 10.1093/pcmedi/pbad001

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© The Author(s) 2023. Published by Oxford University Press on behalf of the West China School of Medicine & West China Hospital of Sichuan University.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Figure 3. — Evaluation of the deep-learning model based on ferroptosis-related genes. Kaplan–Meier survival analysis of disease-free survival stratified by DLF_score for prostate cancer patients (A) without and (B) with positive surgical margin in the TCGA cohort. Different distributions of DLF_score among patients with different Gleason scores in (C) the TCGA cohort and (D) the GSE116918 cohort. Distribution of DLF_score among patients with different tumor stages in (E) the TCGA cohort and (F) the GSE116918 cohort. (G) Kaplan–Meier survival analysis of disease-free survival stratified by DLF_score for pan-cancer patients from the TCGA data set. (H) Cox regression analysis of the deep learning-based model in different kinds of malignancies. TCGA, The Cancer Genome Atlas; DLF_score, deep learning-based ferroptosis score; HR, hazard ratio.