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. Devel...
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| Drugi avtorji: | , , , , , |
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| Format: | Elektronski Book Chapter |
| Jezik: | angleščina |
| Izdano: |
Springer Nature
2020
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| Teme: | |
| Online dostop: | DOAB: download the publication DOAB: description of the publication |
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| Izvleček: | 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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| Fizični opis: | 1 electronic resource (475 p.) |
| ISBN: | 978-3-030-47994-7 |
| Dostop: | Open Access |