Leveraging Data Science for Global Health
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. Devel...
| Other Authors: | , , , , , , |
|---|---|
| Format: | eBook |
| Language: | Inglés |
| Published: |
Cham :
Springer Nature
2020
2020. |
| Edition: | 1st ed. 2020. |
| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009428410606719 |
Table of Contents:
- 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.
