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Leveraging Data Science for Global Health

Format: Hardback
Publisher: Springer Nature Switzerland AG, Cham, Switzerland
Published: 1st Aug 2020
Dimensions: w 156mm h 234mm d 27mm
Weight: 857g
ISBN-10: 3030479935
ISBN-13: 9783030479930
Barcode No: 9783030479930
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Synopsis
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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"This book seems to empower the reader to gradually embark on the development of medical applications incorporating data science. ... This book is well structured, written with a good level of linguistic guts, and could be recommended to data science students rather than researchers or health professionals." (Thierry Edoh, Computing Reviews, March 24, 2022)