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Machine Learning for Healthcare - Handling and Managing Data (Hardcover)
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Machine Learning for Healthcare - Handling and Managing Data (Hardcover)
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Machine Learning for Healthcare: Handling and Managing Data
provides in-depth information about handling and managing
healthcare data through machine learning methods. This book
expresses the long-standing challenges in healthcare informatics
and provides rational explanations of how to deal with them.
Machine Learning for Healthcare: Handling and Managing Data
provides techniques on how to apply machine learning within your
organization and evaluate the efficacy, suitability, and efficiency
of machine learning applications. These are illustrated in a case
study which examines how chronic disease is being redefined through
patient-led data learning and the Internet of Things. This text
offers a guided tour of machine learning algorithms, architecture
design, and applications of learning in healthcare. Readers will
discover the ethical implications of machine learning in healthcare
and the future of machine learning in population and patient health
optimization. This book can also help assist in the creation of a
machine learning model, performance evaluation, and the
operationalization of its outcomes within organizations. It may
appeal to computer science/information technology professionals and
researchers working in the area of machine learning, and is
especially applicable to the healthcare sector. The features of
this book include: A unique and complete focus on applications of
machine learning in the healthcare sector. An examination of how
data analysis can be done using healthcare data and bioinformatics.
An investigation of how healthcare companies can leverage the
tapestry of big data to discover new business values. An
exploration of the concepts of machine learning, along with recent
research developments in healthcare sectors.
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