Leveraging Data Science for Global Health
Leo Anthony Celi editor Maimuna S Majumder editor Patricia Ordóñez editor Juan Sebastian Osorio editor Kenneth E Paik editor Melek Somai editor
Format:Hardback
Publisher:Springer Nature Switzerland AG
Published:1st Aug '20
Should be back in stock very soon
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.
“This book seems to empower the reader to gradually embark on the development of medical applications incorporating data science. … This book is well structured, written with a good level of linguistic guts, and could be recommended to data science students rather than researchers or health professionals.” (Thierry Edoh, Computing Reviews, March 24, 2022)
ISBN: 9783030479930
Dimensions: unknown
Weight: unknown
475 pages
1st ed. 2020