A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION

Cancer detection from gene expression data continues to pose a challenge due to the high dimensionality and complexity of these data. After decades of research there is still uncertainty in the clinical diagnosis of cancer and the identification of tumor-specific markers. Here we present a deep lear...

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Vydané v:	Biocomputing 2017 Ročník 22; s. 219 - 229
Hlavní autori:	DANAEE, PADIDEH, GHAEINI, REZA, HENDRIX, DAVID A.
Médium:	Kapitola Journal Article
Jazyk:	English
Vydavateľské údaje:	United States WORLD SCIENTIFIC 01.01.2017
Predmet:	Algorithms Biomarkers, Tumor - genetics Breast Neoplasms - classification Breast Neoplasms - diagnosis Breast Neoplasms - genetics Computational Biology Databases, Genetic - statistics & numerical data Female Gene Expression Profiling - statistics & numerical data Gene Ontology Humans PATTERNS IN BIOMEDICAL DATA-HOW DO WE FIND THEM? Principal Component Analysis Supervised Machine Learning Stacked Denoising Autoencoder Dimensionality Reduction Cancer Detection RNA-seq Expression Deep Learning Classification
ISBN:	9789813207820, 9789813207806, 9813207825, 9813207809, 9789813207813, 9813207817
ISSN:	2335-6936
On-line prístup:	Získať plný text
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