Leveraging Data Science for Global Health

• Other Authors: Celi, Leo Anthony (Editor), Majumder, Maimuna S. (Editor), Ordóñez, Patricia (Editor), Osorio, Juan Sebastian (Editor), Paik, Kenneth E. (Editor), Somai, Melek (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Springer Nature 2020
• Subjects: Medical equipment & techniques; Health & safety aspects of IT; Health economics; Health Informatics; Health Economics; Open Access; Big Data; Machine Learning; Artificial Intelligence; Digital Disease Surveillance; Health Mapping; Health Records for Non-Communicable Diseases; HealthMap; Tools for Clinical Trials; Information technology: general issues
• Online Access: DOAB: download the publication; DOAB: description of the publication

Summary

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.

Physical Description

1 electronic resource (475 p.)

ISBN

978-3-030-47994-7

Access

Open Access