Leveraging Data Science for Global Health

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Tác giả: Leo Anthony Celi, Maimuna S Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E Paik, Melek Somai

Ngôn ngữ: eng

ISBN-13: 978-3030479947

Ký hiệu phân loại:

Thông tin xuất bản: Cham, Switzerland : Springer Nature, 2020

Mô tả vật lý: 1 electronic resource (475 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 222564

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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