Demystifying big data and machine learning for healthcare

By:

Natarajan, Prashant

Material type: Text

TextPublication details: Routledge New York 2021Description: xxvi, 183 pISBN:

9781032097169

Subject(s):

DDC classification:

362.1 NAT

Summary: 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.

List(s) this item appears in: Non Fiction

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	362.1 NAT (Browse shelf(Opens below))	1	Available		004749

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Previous	338.927014 MAR Information and communication technology for sustainable development	343.54 CHA Cyber laws and IT protection	361.3028563 TAM Artificial intelligence and social work	362.1 NAT Demystifying big data and machine learning for healthcare	362.1 UND Health tech:	362.10684 MAD Data-driven healthcare: how analytics and BI are transforming the industry	363.25968 HAS Digital forensics basics:	Next

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.

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