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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| Beste egile batzuk: | , , , , , |
| Formatua: | Baliabide elektronikoa eBook |
| Hizkuntza: | ingelesa |
| Argitaratua: |
Cham :
Springer International Publishing : Imprint: Springer,
2020.
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| Edizioa: | 1st ed. 2020. |
| Gaiak: | |
| Sarrera elektronikoa: | Link to Metadata |
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| Gaia: | 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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| Deskribapen fisikoa: | XII, 475 p. 196 illus., 175 illus. in color. online resource. |
| ISBN: | 9783030479947 |
| DOI: | 10.1007/978-3-030-47994-7 |
| Sartu: | Open Access |