Handbook on Intelligent Healthcare Analytics: Knowledge Engineering with Big Data

The book explores the various recent tools and techniques used for  deriving knowledge from healthcare data analytics for researchers and  practitioners.

The power of healthcare data analytics is being  increasingly used in the industry. Advanced analytics techniques are  used against large data sets to uncover hidden patterns, unknown  correlations, market trends, customer preferences, and other useful  information.

A Handbook on Intelligent Healthcare Analytics  covers both the theory and application of the tools, techniques, and  algorithms for use in big data in healthcare and clinical research. It  provides the most recent research findings to derive knowledge using big  data analytics, which helps to analyze huge amounts of real-time  healthcare data, the analysis of which can provide further insights in  terms of procedural, technical, medical, and other types of improvements  in healthcare.

In addition, the reader will find in this Handbook:
Innovative  hybrid machine learning and deep learning techniques applied in various  healthcare data sets, as well as various kinds of machine learning  algorithms existing such as supervised, unsupervised, semi-supervised,  reinforcement learning, and guides how readers can implement the Python  environment for machine learning;An exploration of predictive analytics  in healthcare;The various challenges for smart healthcare, including  privacy, confidentiality, authenticity, loss of information, attacks,  etc., that create a new burden for providers to maintain compliance with  healthcare data security. In addition, this book also explores various  sources of personalized healthcare data and the commercial platforms for  healthcare data analytics.
Audience
Healthcare professionals,  researchers, and practitioners who wish to figure out the core concepts  of smart healthcare applications and the innovative methods and  technologies used in healthcare will all benefit from this book.