Publication Date:
2021-02-10
Description:
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.
Keywords:
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
;
Medical equipment & techniques
;
Information technology: general issues
;
Health & safety aspects of IT
;
Health economics
;
bic Book Industry Communication::M Medicine::MB Medicine: general issues::MBG Medical equipment & techniques
;
bic Book Industry Communication::U Computing & information technology::UB Information technology: general issues::UBH Health & safety aspects of IT
;
bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCQ Health economics
Language:
English
Format:
image/jpeg
