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Springer Health Informatics Data Analysis: Methods and Examples

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Description

This comprehensive guide explores biomedical data analysis across clinical and genomic datasets, offering practical methods for healthcare professionals and researchers. The book covers electrocardiograms, EEG analysis, Big Data health mining, and mass spectrometry imaging techniques with detailed explanations and sample analyses in each chapter. You'll discover how to apply healthcare information association rules, understand telehealth infrastructure implementation, and leverage data mining for health outcomes. Whether you're working with functional disease data or environmental biodiversity records, this Health Information Science resource provides the methods and real-world examples needed to extract meaningful insights from complex health datasets and improve decision-making in clinical and research environments.

Key Features

Covers multiple biomedical data types including clinical data, genomic data, electrocardiograms, and EEG analysis with practical examples.

Includes detailed chapters on Big Data health mining techniques and mass spectrometry imaging methods for healthcare applications.

Each chapter provides field summaries and sample analyses to help readers understand and apply health informatics methods.

Addresses healthcare information association rules and telehealth infrastructure for modern health systems.

Published by Springer as part of the Health Information Science series for academic and professional reference.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
10 August 2018
Listed Since
13 August 2018

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