Learning from small medical data—robust semi-supervised cancer prognosis classifier with Bayesian variational autoencoder

Abstract Motivation Cancer is one of the world’s leading mortality causes, and its prognosis is hard to predict due to complicated biological interactions among heterogeneous data types. Numerous challenges, such as censorship, high dimensionality and small sample size, prevent researchers from usin...

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Veröffentlicht in:	Bioinformatics advances Jg. 3; H. 1; S. vbac100
Hauptverfasser:	Hsu, Te-Cheng, Lin, Che
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Oxford University Press 2023
Schlagworte:	Bayesian analysis Bioinformatics Breast cancer Deep learning Mathematical models Medical prognosis Neural networks Non-small cell lung carcinoma Original Paper Precision medicine Prognosis Small cell lung carcinoma
ISSN:	2635-0041, 2635-0041
Online-Zugang:	Volltext
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