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Strategies in Biomedical Data Science

An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals;

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Large-Scale Biomedical Science

Science: Exploring Strategies for Research looks at the role of these new large-scale projects in the biomedical sciences. Though written by the;

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Data Handling and Analysis

cytopathology to transfusion science. Data Handling and Analysis is the most relevant and useful statistics and data analysis text for biomedical;

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Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering;

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Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;

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Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques

Quantitative biomedical data analysis is a fast-growing interdisciplinary area of applied and computational mathematics, statistics;

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Statistical Modeling in Biomedical Research

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their;

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Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications;

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Data Science and Predictive Analytics

strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic;

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Deep Learning for Data Analytics

of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications;

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Biomedical Science Handbook

Applied natural sciences such as clinical virology, medical microbiology, genetic epidemiology, clinical epidemiology and biomedical;

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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Introduction To The Science Of Medical Imaging

biomedical imaging an essential tool in clinical medicine and biomedical research. Key technological advances include MRI, positron emission;

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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Advances in Biomedical Science

Biomedical sciences refer to a group of applied sciences that apply aspects of natural science for use in healthcare and public health;

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Interpreting Biomedical Science

Interpreting Biomedical Science: Experiment, Evidence, and Belief discusses what can go wrong in biological science, providing an unbiased;

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Biomedical Signal Processing

big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include;

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Biomedical Applications of Nanoparticles

Biomedical Applications of Nanoparticles describes the most interesting and investigated biomedical applications of nanoparticles;

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Applied Mathematics in Biomedical Science

Biomedical science is the set of applied sciences that has applications in developing technology that can be of use in public health or;

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Biomedical Science Practice

Biomedical scientists are the foundation of modern healthcare, from cancer screening to diagnosing HIV, from blood transfusion for surgery;

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Two-Dimensional Nanostructures for Biomedical Technology

Two Dimensional Nanostructures for Biomedical Technology: A Bridge between Materials Science and Bioengineering helps researchers to;

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Principles of Biomedical Informatics

the storage, retrieval, and use of biomedical data for biological problem solving and medical decision making. It covers the application;

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From Bioinspired Systems and Biomedical Applications to Machine Learning

applications domains, as biomedical systems, or big data solutions.;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis;

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Data Science and Its Applications

vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful;

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Mining the Biomedical Literature

of biomedical text available The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological;

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Logic and Critical Thinking in the Biomedical Sciences

Thinking in the Biomedical Sciences invites readers to linger over a collection of common observations to see what inferences can be drawn, when;

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