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Kernel mixture survival models for identifying cancer subtypes, predicting patient's cancer types and survival probabilities.

Genome informatics. International Conference on Genome Informatics - 1 Jan 2004

Ando Tomohiro, Imoto Seiya, Miyano Satoru

Abstract excerpt

One important application of microarray gene expression data is to study the relationship between the clinical phenotype of cancer patients and gene expression profiles on the whole-genome scale. The clinical phenotype includes several different types of cancers, survival times, relapse times, drug responses and so on. Under the situation that the subtypes of cancer have not been previously identified or known to...

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PMID: 15706506

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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