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Computational medicine in data minin...

Rakocevic, Goran,

Computational medicine in data mining and modeling /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Computational medicine in data mining and modeling // Goran Rakocevic ... [et al.], editors.
其他作者:	Rakocevic, Goran,
出版者:	New York :Springer, : c2013.,
面頁冊數:	x, 376 p. :ill. ; : 24 cm;
標題:	Data mining. -
ISBN:	1461487846 (cloth) :

Computational medicine in data mining and modeling /
Computational medicine in data mining and modeling /Goran Rakocevic ... [et al.], editors. - New York :Springer,c2013. - x, 376 p. :ill. ;24 cm

Includes bibliographical references.

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.

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. --

ISBN: 1461487846 (cloth) :NT3802

LCCN: 2013950376Subjects--Topical Terms:

528622
Data mining.

LC Class. No.: R858 / .C6244 2013

Dewey Class. No.: 610.285

Computational medicine in data mining and modeling /
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020 $a 9781461487845 (cloth)
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035 $a (OCoLC)ocn868900433
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245 1 0 $a Computational medicine in data mining and modeling / $c Goran Rakocevic ... [et al.], editors.
260 # $a New York : $c c2013. $b Springer,
300 $a x, 376 p. : $b ill. ; $c 24 cm
504 $a Includes bibliographical references.
505 0 # $a 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.
520 # $a 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. -- $c Source other than Library of Congress
650 # 0 $a Data mining. $3 528622
650 # 0 $a Medical informatics. $3 583858
700 1 # $a Rakocevic, Goran, $e editor of compilation. $3 981609