Leo Anthony Celi (ed.); Maimuna S. Majumder (ed.); Patricia Ordóñez (ed.); Juan Sebastian Osorio (ed.); Kenneth E. (ed Paik Springer (2020) Kovakantinen kirja
Leo Anthony Celi (ed.); Maimuna S. Majumder (ed.); Patricia Ordóñez (ed.); Juan Sebastian Osorio (ed.); Kenneth E. (ed Paik Springer (2020) Pehmeäkantinen kirja
Springer Sivumäärä: 475 sivua Asu: Kovakantinen kirja Julkaisuvuosi: 2020, 01.08.2020 (lisätietoa) Kieli: Englanti
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.