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Leveraging Data Science for Global Health
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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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Keywords
- artificial intelligence
- big data
- Computing & information technology
- Digital Disease Surveillance
- Economics
- Economics, finance, business & management
- Health & safety aspects of IT
- Health Economics
- Health Informatics
- Health Mapping
- Health Records for Non-Communicable Diseases
- HealthMap
- Information technology: general issues
- Machine learning
- Medical equipment & techniques
- medicine
- Medicine: General Issues
- open access
- Tools for Clinical Trials
Links
DOI: 10.1007/978-3-030-47994-7Editions