TY  - BOOK
ED  - Celi, Leo Anthony
ED  - Majumder, Maimuna S.
ED  - Ordóñez, Patricia
ED  - Osorio, Juan Sebastian
ED  - Paik, Kenneth E.
ED  - Somai, Melek
AB  - 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.
DO  - 10.1007/978-3-030-47994-7
ID  - OAPEN ID: ONIX_20200813_9783030479947_32
KW  - Health Informatics
KW  - Health Economics
KW  - Open Access
KW  - Big Data
KW  - Machine Learning
KW  - Artificial Intelligence
KW  - Digital Disease Surveillance
KW  - Health Mapping
KW  - Health Records for Non-Communicable Diseases
KW  - HealthMap
KW  - Tools for Clinical Trials
KW  - Medical equipment & techniques
KW  - Information technology: general issues
KW  - Health & safety aspects of IT
KW  - Health economics
L1  - https://library.oapen.org/bitstream/id/98a19deb-6720-40bf-b6ec-fd7674e09c39/2020_Book_LeveragingDataScienceForGlobal.pdf
LA  - English
LK  - https://library.oapen.org/handle/20.500.12657/41290
PB  - Springer Nature
PY  - 2020
TI  - Leveraging Data Science for Global Healthnull
ER  - 
