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Leveraging Data Science for Global Health

Authors: --- --- --- --- et al.
ISBN: 9783030479947 Year: Pages: 475 DOI: 10.1007/978-3-030-47994-7 Language: English
Publisher: Springer Nature
Subject: Medicine (General) --- Computer Science --- Economics
Added to DOAB on : 2020-09-01 00:01:25
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Abstract

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.

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