Fig. 2: Kaplan–Meier survival analysis of the cancer-segmented area 20× magnification multiple instance learning model (PathoRiCH). | Nature Communications

Fig. 2: Kaplan–Meier survival analysis of the cancer-segmented area 20× magnification multiple instance learning model (PathoRiCH).

From: Histopathologic image–based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer

Fig. 2

Two-sided Kaplan–Meier survival analysis was used. a In the internal validation, the PathoRiCH-predicted favorable and poor groups exhibited significant differences in the platinum-free interval (PFI) and overall survival (OS) (p = 4.17E-05 and p = 8.73E-05, respectively). b Analysis of the TCGA external validation cohort revealed significant patient stratification for PFI (p = 0.032) and OS (p = 1.06E-09). c The SMC external validation cohort also showed significant patient stratification for PFI (p = 0.030), but it did not reach statistical significance for OS (p = 0.54).

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