Article

DeepGliomaAI: A Variational Autoencoder Framework for Interpretable Transcriptomic Representation and Prognostic Stratification in Glioma

2026-05-26

Abstract excerpt

<title>Abstract</title> <p>Background: Gliomas are biologically heterogeneous primary brain tumours whose molecular diversity extends well beyond current diagnostic markers. Variational Autoencoders (VAEs) offer a principled framework for learning compact, probabilistically regularised latent representations from high-dimensional transcriptomic data without clinical supervision. <h4>Methods:</h4> We trained a VAE...

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Literature Corpus work: ed773e8d-e005-55c8-8940-e08226e12baa
DOI: 10.21203/rs.3.rs-9808350/v1

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