Computational Medicine in Data Mining and Modeling / edited by Goran Rakocevic, Tijana Djukic, Nenad Filipovic, Veljko Milutinović.

Format:

Book

Contributor:

Rakocevic, Goran, editor.

Djukic, Tijana, editor.

Filipović, Nenad, editor.

Milutinović, Veljko, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Language:

English

Subjects (All):

Data mining.

Bioinformatics.

Artificial intelligence.

Computer simulation.

Data Mining and Knowledge Discovery.

Computational Biology/Bioinformatics.

Artificial Intelligence.

Simulation and Modeling.

Local Subjects:

Data Mining and Knowledge Discovery.

Computational Biology/Bioinformatics.

Artificial Intelligence.

Simulation and Modeling.

Physical Description:

1 online resource (X, 376 pages) : 171 illustrations, 128 illustrations in color

Edition:

First edition 2013.

Contained In:

Springer eBooks

Place of Publication:

New York, NY : Springer New York : Imprint: Springer, 2013.

System Details:

text file PDF

Summary:

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient's medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more. This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter. Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

Contents:

Mining Clinical Data

Applications of probabilistic and related logics to decision support in medicine

Transforming electronic medical books to diagnostic decision support systems using relational database management systems

Text mining in medicine

A primer on information theory, with applications to neuroscience

Machine Learning based Imputation of Missing SNP Genotypes in SNP Genotype Arrays

Computer modeling of atherosclerosis

Particle dynamics and design of nano-drug delivery systems

Computational Modeling of Ultrasound Wave Propagation in Bone.

Other Format:

Printed edition:

ISBN:

978-1-4614-8785-2

9781461487852

Access Restriction:

Restricted for use by site license.