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Leveraging data science for global health

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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Detail Information
Series Title
-
Call Number
362.10285 LEO l
Publisher
Switzerland : Springer Cham.,
Collation
XII, 475 p
Language
English
ISBN/ISSN
9783030479947
Classification
NONE
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
big data
Data mining
Medical informatics
World health
Internet in medicine
Medical economic
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

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