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Leveraging Data Science for Global Health [[electronic resource] /] / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai



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Autore: Celi Leo Anthony Visualizza persona
Titolo: Leveraging Data Science for Global Health [[electronic resource] /] / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai Visualizza cluster
Pubblicazione: Springer Nature, 2020
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Edizione: 1st ed. 2020.
Descrizione fisica: 1 online resource (XII, 475 p. 196 illus., 175 illus. in color.)
Disciplina: 502.85
Soggetto topico: Health informatics
Health economics
Health Informatics
Health Economics
Soggetto non controllato: 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
Persona (resp. second.): CeliLeo Anthony
MajumderMaimuna S
OrdóñezPatricia
OsorioJuan Sebastian
PaikKenneth E
SomaiMelek
Nota di contenuto: Part 1: Big Data and Global Health Landscape -- Chapter 1. Strengths and Weaknesses of Big Data for Global Health Surveillance -- Chapter 2. Opportunities for Health Big Data in Africa -- Chapter 3. HealthMap and Digital Disease Surveillance -- Chapter 4. Mobility Data and Genomics for Disease Surveillance -- Part 2: Case Studies -- Chapter 5. Kumbh Mela Disease Surveillance -- Chapter 6. Using Google Mobility Data for Disaster Monitoring in Puerto Rico -- Chapter 7. StreetRx and the Opioid Epidemic -- Chapter 8. Twitter Data for Zika Virus Surveillance in Venezuela -- Chapter 9. Hepatitis E Outbreak in Namibia and Google Trends -- Chapter 10. Patient-Controlled Health Records for Non-Communicable Diseases in Humanitarian Settings -- Chapter 11. Addressing Sexual and Reproductive Health among Youth Migrants -- Chapter 12. Tanzanian cholera: epidemic or endemic? -- Chapter 13. Google Satellite Images to Predict Yellow Fever Incidence in Brazil -- Chapter 14. Feature Selection and Prediction of Treatment Failure in Tuberculosis -- Chapter 15. Tuberculosis, Refugees, and the Politics of Journalistic Objectivity: A qualitative review using HealthMap data -- Chapter 16. Designing Tools to Support the Cutaneous Leishmaniasis Trial in Colombia.
Sommario/riassunto: 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.
Titolo autorizzato: Leveraging Data Science for Global Health  Visualizza cluster
ISBN: 3-030-47994-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996465446903316
Lo trovi qui: Univ. di Salerno
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