A network-constrain Weibull AFT model for biomarkers discovery
- URL: http://arxiv.org/abs/2402.18242v1
- Date: Wed, 28 Feb 2024 11:12:53 GMT
- Title: A network-constrain Weibull AFT model for biomarkers discovery
- Authors: Claudia Angelini, Daniela De Canditiis, Italia De Feis, Antonella
Iuliano
- Abstract summary: AFTNet is a network-constraint survival analysis method based on the Weibull accelerated failure time (AFT) model.
We present an efficient iterative computational algorithm based on the proximal descent gradient method.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We propose AFTNet, a novel network-constraint survival analysis method based
on the Weibull accelerated failure time (AFT) model solved by a penalized
likelihood approach for variable selection and estimation. When using the
log-linear representation, the inference problem becomes a structured sparse
regression problem for which we explicitly incorporate the correlation patterns
among predictors using a double penalty that promotes both sparsity and
grouping effect. Moreover, we establish the theoretical consistency for the
AFTNet estimator and present an efficient iterative computational algorithm
based on the proximal gradient descent method. Finally, we evaluate AFTNet
performance both on synthetic and real data examples.
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