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Biology, medicine and biochemistry have become data-centric fields
for which Deep Learning methods are delivering groundbreaking
results. Addressing high impact challenges, Deep Learning in
Biology and Medicine provides an accessible and organic collection
of Deep Learning essays on bioinformatics and medicine. It caters
for a wide readership, ranging from machine learning practitioners
and data scientists seeking methodological knowledge to address
biomedical applications, to life science specialists in search of a
gentle reference for advanced data analytics.With contributions
from internationally renowned experts, the book covers foundational
methodologies in a wide spectrum of life sciences applications,
including electronic health record processing, diagnostic imaging,
text processing, as well as omics-data processing. This survey of
consolidated problems is complemented by a selection of advanced
applications, including cheminformatics and biomedical interaction
network analysis. A modern and mindful approach to the use of
data-driven methodologies in the life sciences also requires
careful consideration of the associated societal, ethical, legal
and transparency challenges, which are covered in the concluding
chapters of this book.
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