Muutke küpsiste eelistusi

Computational Medicine in Data Mining and Modeling Softcover reprint of the original 1st ed. 2013 [Pehme köide]

Edited by , Edited by , Edited by , Edited by
  • Formaat: Paperback / softback, 376 pages, kõrgus x laius: 235x155 mm, kaal: 5854 g, 128 Illustrations, color; 43 Illustrations, black and white; X, 376 p. 171 illus., 128 illus. in color., 1 Paperback / softback
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1493948342
  • ISBN-13: 9781493948345
  • Pehme köide
  • Hind: 104,29 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 122,69 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
  • Formaat: Paperback / softback, 376 pages, kõrgus x laius: 235x155 mm, kaal: 5854 g, 128 Illustrations, color; 43 Illustrations, black and white; X, 376 p. 171 illus., 128 illus. in color., 1 Paperback / softback
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1493948342
  • ISBN-13: 9781493948345
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 patients 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.
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.