Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques

By: Don Hong (Editor), Yu Shyr (Editor)

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Hardcover | 11 July 2007

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Hardcover
364 Pages

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22.86 x 15.24 x 1.91

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Quantitative biomedical data analysis is a fast-growing interdisciplinary area of applied and computational mathematics, statistics, computer science, and biomedical science, leading to new fields such as bioinformatics, biomathematics, and biostatistics. In addition to traditional statistical techniques and mathematical models using differential equations, new developments with a very broad spectrum of applications, such as wavelets, spline functions, curve and surface subdivisions, sampling, and learning theory, have found their mathematical home in biomedical data analysis.This book gives a new and integrated introduction to quantitative medical data analysis from the viewpoint of biomathematicians, biostatisticians, and bioinformaticians. It offers a definitive resource to bridge the disciplines of mathematics, statistics, and biomedical sciences. Topics include mathematical models for cancer invasion and clinical sciences, data mining techniques and subset selection in data analysis, survival data analysis and survival models for cancer patients, statistical analysis and neural network techniques for genomic and proteomic data analysis, wavelet and spline applications for mass spectrometry data preprocessing and statistical computing.

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You Can Find This Book In

Non-Fiction Medicine Medicine in General Health Systems & Services Public Health & Preventive Medicine Epidemiology & Medical Statistics Engineering & Technology Technology in General Maths for Engineers Science Science in General Maths for Scientists

Computing & I.T.Databases Data Mining Booktopia Publisher Services World Scientific Publishing

Preface	p. V
Statistical Methodology and Stochastic Modeling
An Overview on Variable Selection for Longitudinal Data	p. 3
Some Recent Results in Model Selection	p. 25
Some State Space Models of AIDS Epidemiology in Homosexual Populations	p. 43
Stochastic and State Space Models of Carcinogenesis: Some New Modeling Approaches	p. 61
Semiparametric Methods for Data from an Outcome-Dependent Sampling Scheme	p. 93
Proteomics and Genomics
Automated Peak Identification in a TOF-MS Spectrum	p. 113
Microarray Data Analysis in Affymetrix Gene Chip	p. 133
Wavelets and Projecting Spectrum Binning for Proteomic Data Processing	p. 159
Survival Modeling and Analysis
Application of the Non-Proportional Rates Model to Recurrent Event Data: Analysis of Risk Factors for Pre-School Asthma	p. 181
Survival Model and Estimation for Lung Cancer Patients	p. 201
Nonparametric Regression Techniques in Survival Analysis	p. 223
Mathematical Models for Diseases
Eigenslope Method for Second-Order Parabolic Partial Differential Equations and the Special Case of Cylindrical Cellular Structures with Spatial Gradients in Membrane Capacitance	p. 255
Mathematical Modelling of Non-Invasive Pressure Support Ventilation: Investigation of Tidal Volume Instability	p. 277
Mathematical Models on the Growth of Solid Tumors	p. 297
Computing and Visualization
Artificial Neural Networks for Data Mining and Feature Extraction	p. 321
Multifractal Discrimination Model (MDM) of High-Frequency Pupil Diameter Measurements for Human-Computer Interaction	p. 333
Index	p. 351
Table of Contents provided by Ingram. All Rights Reserved.

Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques

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