Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it.Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to:Develop skills needed to identify and demolish big-data mythsBecome an expert in separating hype from realityUnderstand the V’s that matter in healthcare and whyHarmonize the 4 C’s across little and big dataChoose data fi delity over data qualityLearn how to apply the NRF Framework Master applied machine learning for healthcareConduct a guided tour of learning algorithmsRecognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs)The variety of d

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