Big Data Analytics in Oncology with R 1st Edition

Big Data Analytics in Oncology with R serves the analytical approaches for big data analysis. There is huge progressed in advanced computation with R. But there are several technical challenges faced to work with big data. These challenges are with computational aspect and work with fastest way to get computational results. Clinical decision through genomic information and survival outcomes are now unavoidable in cutting-edge oncology research. This book is intended to provide a comprehensive text to work with some recent development in the area.

Features:

Covers gene expression data analysis using R and survival analysis using R
Includes bayesian in survival-gene expression analysis
Discusses competing-gene expression analysis using R
Covers Bayesian on survival with omics data

This book is aimed primarily at graduates and researchers studying survival analysis or statistical methods in genetics.

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Description

Big Data Analytics in Oncology with R 1st Edition

by Atanu Bhattacharjee (Author)

Focus on Big Data and Computational Challenges: Addresses the technical challenges of working with large datasets in oncology, particularly in terms of computational efficiency and methods for obtaining rapid results.
Gene Expression Analysis with R: Provides comprehensive coverage of gene expression data analysis using R, offering practical insights for analyzing large genomic datasets.
Survival Analysis with R: Detailed exploration of survival analysis techniques using R, which is crucial for understanding patient outcomes and survival predictions.
Bayesian Methods: Includes discussions on Bayesian approaches in survival and gene expression analysis, an essential statistical framework for modeling uncertainty in big data.
Competing Gene Expression Analysis: Covers competing-gene expression analysis, helping to identify and analyze competing risk factors in oncology data.

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