Article

Stratified neural networks in a time-to-event setting

2021-02-02

Abstract excerpt

Deep neural networks are now frequently employed to predict survival conditional on omics-type biomarkers, e.g. by employing the partial likelihood of Cox proportional hazards model as loss function. Due to the generally limited number of observations in clinical studies, combining different data-sets has been proposed to improve learning of network parameters. However, if baseline hazards differ between the studi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 061623cf-e48f-5c9d-b582-dfac9683c64b
DOI: 10.1101/2021.02.01.429169

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Stratified neural networks in a time-to-event settingDOI 10.1101/2021.02.01.429169Read

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival modelsSemantic proximity Read

AUTOSurv: Interpretable Deep Learning Framework for Cancer Survival Analysis Incorporating Clinical and Multi-omics DataSemantic proximity Read

A Transformer-Based Approach to Survival Outcome PredictionSemantic proximity Read

Cox-nnet: an artificial neural network method for prognosis prediction on high-throughput omics dataSemantic proximity Read

Unified Methods for Feature Selection in Large-Scale Genomic Studies with Censored Survival OutcomesSemantic proximity Read

DeepGliomaAI: A Variational Autoencoder Framework for Interpretable Transcriptomic Representation and Prognostic Stratification in GliomaSemantic proximity Read

Tabular Foundation Model for Breast Cancer Prognosis using Gene Expression DataSemantic proximity Read

Identification of Monotonically Classifying Pairs of Genes for Ordinal Disease OutcomesSemantic proximity Read

Learning to train and to explain a deep survival model with large scale ovarian cancer transcriptomic dataSemantic proximity Read

PINT: Pathway-pathway interactions for predicting interpretable clinical outcomes from gene expressionSemantic proximity Read

GenoPath-MCA: Multimodal masked cross-attention between genomics and pathology for survival predictionSemantic proximity Read

PathX-CNN: An Enhanced Explainable Convolutional Neural Network for Survival Prediction and Pathway Analysis in GlioblastomaSemantic proximity Read