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This book introduces readers to the methods, types of data, and
scale of analysis used in the context of health. The challenges of
working with big data are explored throughout the book, while the
benefits are also emphasized through the discoveries made possible
by linking large datasets. Methods include thorough case studies
from statistics, as well as the newest facets of data analytics:
data visualization, modeling and simulation, and machine learning.
The diversity of datasets is illustrated through chapters on
networked data, image processing, and text, in addition to typical
structured numerical datasets. While the methods, types of data,
and scale have been individually covered elsewhere, by bringing
them all together under one "umbrella" the book highlights
synergies, while also helping scholars fluidly switch between tools
as needed. New challenges and emerging frontiers are also
discussed, helping scholars grasp how methods will need to change
in response to the latest challenges in health.
This book introduces readers to the methods, types of data, and
scale of analysis used in the context of health. The challenges of
working with big data are explored throughout the book, while the
benefits are also emphasized through the discoveries made possible
by linking large datasets. Methods include thorough case studies
from statistics, as well as the newest facets of data analytics:
data visualization, modeling and simulation, and machine learning.
The diversity of datasets is illustrated through chapters on
networked data, image processing, and text, in addition to typical
structured numerical datasets. While the methods, types of data,
and scale have been individually covered elsewhere, by bringing
them all together under one "umbrella" the book highlights
synergies, while also helping scholars fluidly switch between tools
as needed. New challenges and emerging frontiers are also
discussed, helping scholars grasp how methods will need to change
in response to the latest challenges in health.
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