Learning to Train and to Explain a Deep Survival Model with Large-Scale Ovarian Cancer Transcriptomic Data

Learning to Train and to Explain a Deep Survival Model with Large-Scale Ovarian Cancer Transcriptomic Data

<b>Background/Objectives:</b> Ovarian cancer is a complex disease with poor outcomes that affects women worldwide. The lack of successful therapeutic options for this malignancy has led to the need to identify novel biomarkers for patient stratification. Here, we aim to develop the outco...

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Main Authors: Elena Spirina Menand, Manon De Vries-Brilland, Leslie Tessier, Jonathan Dauvé, Mario Campone, Véronique Verrièle, Nisrine Jrad, Jean-Marie Marion, Pierre Chauvet, Christophe Passot, Alain Morel
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Biomedicines
Subjects:
TCGA
ovarian cancer
RNA-seq
survival analysis
deep learning
molecular pathways
Online Access:https://www.mdpi.com/2227-9059/12/12/2881
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