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Medical Data Sharing, Harmonization and Analytics

Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data;

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Biomedical Data Management and Graph Online Querying

information retrieval and data analytics for electronic medical records; data management and visualization of medical data; biomedical data sharing;

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Data Analytics in Biomedical Engineering and Healthcare

in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and;

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Sharing Economy and Big Data Analytics

necessary for businesses of this economy and proposes a series of useful applications that illustrate the use of data in the sharing ecosystem.;

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Healthcare Data Analytics

applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support;

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Big Data Analytics

organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical;

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Big Data Analytics in Cognitive Social Media and Literary Texts

This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition;

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Risky Business

Due to the digitization of medical records, more and more health data is readily available. This dynamic has created many opportunities to;

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Meta-Analytics

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use;

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Big Data and Knowledge Sharing in Virtual Organizations

corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing;

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New Perspectives in Medical Records

integration and sharing of patient information, data visualization, big data analytics, and the requirements of modern electronic health records. The;

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Practical Predictive Analytics and Decisioning Systems for Medicine

With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are;

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Brain Informatics and Health

technologies and systems; analysis of complex medical data; understanding of information processing in brain; neuroimaging data processing strategies;

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Big Data Analytics in Bioinformatics and Healthcare

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge;

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Machine Learning Paradigms

parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data;

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Artificial Intelligence and Big Data Analytics for Smart Healthcare

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved;

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Digital Health and Medical Analytics

This book constitutes selected and revised papers from the Second International Conference on Digital Health and Medical Analytics, DHA;

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Machine Learning, Big Data, and IoT for Medical Informatics

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics;

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Medical Big Data and Internet of Medical Things

Big data and the Internet of Things (IoT) play a vital role in prediction systems used in biological and medical applications, particularly;

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Medical Data Privacy Handbook

This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts;

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Analytics in Healthcare: A Practical Introduction

drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use;

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Intuition, Trust, and Analytics

, are important in a data-driven environment to also inform decision making. The third element, trust, is critical for knowledge sharing to take;

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Intuition, Trust, and Analytics

, are important in a data-driven environment to also inform decision making. The third element, trust, is critical for knowledge sharing to take;

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Green Computing and Predictive Analytics for Healthcare

in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve;

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Big Data, Mining, and Analytics

mining and the transforming of unstructured data into useful information Examines real time wireless medical data acquisition for today's;

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Big Data, Mining, and Analytics

mining and the transforming of unstructured data into useful information Examines real time wireless medical data acquisition for today's;

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Healthcare Analytics

administrators in nursing and public health, as well as medical students who are interested in the future of data within healthcare.;

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