Leveraging Data Science for Global Health (Hardcover, 1st ed. 2020)

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure - and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources - including news media, social media, Google Trends, and Google Street View - can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	August 2020
First published:	2020
Editors:	Leo Anthony Celi • Maimuna S. Majumder • Patricia Ordonez • Juan Sebastian Osorio • Kenneth E. Paik • Melek Somai
Dimensions:	235 x 155 x 36mm (L x W x T)
Format:	Hardcover
Pages:	475
Edition:	1st ed. 2020
ISBN-13:	978-3-03-047993-0
Categories:	Books > Business & Economics > Economics > General Books > Computing & IT > Social & legal aspects of computing > Health & safety aspects of computing Books > Medicine > General issues > Medical equipment & techniques > General Books > Medicine > General issues > Health systems & services > General
LSN:	3-03-047993-5
Barcode:	9783030479930

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