Knowledge of transcription of the human genome might greatly enhance our understanding
of cancer. In particular, gene expression may be used to predict the survival of cancer …

Small cell lung cancers (SCLCs) and extrapulmonary small cell cancers (SCCs) are very
aggressive tumors arising de novo as primary small cell cancer with characteristic genetic …

Purpose: One of the main challenges of lung cancer research is identifying patients at high
risk for recurrence after surgical resection. Simple, accurate, and reproducible methods of …

With the development of high-throughput biological techniques, high-dimensional omics
data have emerged. These molecular data provide a solid foundation for precision medicine …

The development of molecular signatures for the prediction of time-to-event outcomes is a
methodologically challenging task in bioinformatics and biostatistics. Although there are …

Data extracted from microarrays are now considered an important source of knowledge
about various diseases. Several studies based on microarray data and the use of receiver …

For neuroblastoma, the most common extracranial tumour of childhood, identification of new
biomarkers and potential therapeutic targets is mandatory to improve risk stratification and …

Motivation: There has been an increasing interest in expressing a survival phenotype (eg
time to cancer recurrence or death) or its distribution in terms of a subset of the expression …

Background Microarray technology is increasingly used to identify potential biomarkers for
cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian …

This article proposes a Bayesian neural network approach to determine the risk of re-
intervention after endovascular aortic aneurysm repair surgery. The target of proposed …