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Computational Medicine in Data Mining and Modeling

. Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced;

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Advances in Bioinformatics and Computational Biology

, including sequence analysis; motifs, and pattern matching; biological databases, data management, data integration, and data mining; biomedical text;

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Computational Systems Bioinformatics - Methods And Biomedical Applications

by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents;

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Lecture Notes in Computational Intelligence and Decision Making

Information and computer technologies for data analysis and processing in various fields of data mining and machine learning generates the;

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Computational Bioengineering and Bioinformatics

-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and;

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Computational Bioengineering and Bioinformatics

-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and;

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Big Data Analytics

big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.;

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Lecture Notes in Computational Intelligence and Decision Making

This book includes 46 scientific papers presented at the conference and reflecting the latest research in the fields of data mining;

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Complex Systems and Computational Biology Approaches to Acute Inflammation

volume provide an introduction to different types of computational modeling, and how these methods can be applied to specific inflammatory;

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Evolutionary Computation Machine Learning and Data Mining in Bioinformatics

This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining;

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Financial Decision Making Using Computational Intelligence

. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data;

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Predictive Modeling of Drug Sensitivity

mathematical and computational approaches to biological problemsCovers all aspects of drug sensitivity modeling, starting from initial data;

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Foundations of Computational Intelligence 06

Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden;

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R and Data Mining

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for;

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Next Generation of Data Mining

Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation;

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Next Generation of Data Mining

Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation;

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Modern Computational Approaches to Traditional Chinese Medicine

approaches such as data mining, semantic reasoning and computational intelligence have emerged as innovative approaches for the reservation and;

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Contrast Data Mining

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and;

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Grid Computing for Bioinformatics and Computational Biology

explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: Bio-ontology and data mining;

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Intelligent Computing Theories and Methodologies

in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big;

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Intelligent Computing Theories and Methodologies

in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big;

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Data Analytics, Computational Statistics, and Operations Research for Engineers

, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications;

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Signal Processing in Medicine and Biology

machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide;

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Multiscale Modeling of Particle Interactions

Computational biology and nanotechnology have become critical elements in particle interactions, especially in biological sciences;

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Mathematical and Numerical Modeling of the Cardiovascular System and Applications

of bioengineering, applied mathematics, computer, computational and data science, and medicine wishing to become involved in the highly fascinating task;

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Mathematical and Computational Oncology

research; Statistical methods and data mining for cancer research (SMDM); Spatio-temporal tumor modeling and simulation (STTMS).;

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Intelligent Information and Database Systems

Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision;

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