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

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...

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Place / Publishing House:Cham : : Springer International Publishing :, Imprint: Springer,, 2020.
Year of Publication:2020
Edition:1st ed. 2020.
Language:English
Physical Description:1 online resource (XII, 475 p. 196 illus., 175 illus. in color.)
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(DE-He213)978-3-030-47994-7
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spelling Celi, Leo Anthony edt
Leveraging Data Science for Global Health / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai.
1st ed. 2020.
Springer Nature 2020
Cham : Springer International Publishing : Imprint: Springer, 2020.
1 online resource (XII, 475 p. 196 illus., 175 illus. in color.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Open Access
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.
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.
Description based on publisher supplied metadata and other sources.
English
Health informatics.
Health economics.
Health Informatics. https://scigraph.springernature.com/ontologies/product-market-codes/H28009
Health Informatics. https://scigraph.springernature.com/ontologies/product-market-codes/I23060
Health Economics. https://scigraph.springernature.com/ontologies/product-market-codes/W35000
Health Informatics
Health Economics
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
3-030-47993-5
Celi, Leo Anthony. editor. edt http://id.loc.gov/vocabulary/relators/edt
Majumder, Maimuna S. editor. edt http://id.loc.gov/vocabulary/relators/edt
Ordóñez, Patricia. editor. edt http://id.loc.gov/vocabulary/relators/edt
Osorio, Juan Sebastian. editor. edt http://id.loc.gov/vocabulary/relators/edt
Paik, Kenneth E. editor. edt http://id.loc.gov/vocabulary/relators/edt
Somai, Melek. editor. edt http://id.loc.gov/vocabulary/relators/edt
language English
format eBook
author2 Celi, Leo Anthony.
Celi, Leo Anthony.
Majumder, Maimuna S.
Majumder, Maimuna S.
Ordóñez, Patricia.
Ordóñez, Patricia.
Osorio, Juan Sebastian.
Osorio, Juan Sebastian.
Paik, Kenneth E.
Paik, Kenneth E.
Somai, Melek.
Somai, Melek.
author_facet Celi, Leo Anthony.
Celi, Leo Anthony.
Majumder, Maimuna S.
Majumder, Maimuna S.
Ordóñez, Patricia.
Ordóñez, Patricia.
Osorio, Juan Sebastian.
Osorio, Juan Sebastian.
Paik, Kenneth E.
Paik, Kenneth E.
Somai, Melek.
Somai, Melek.
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author_sort Celi, Leo Anthony.
title Leveraging Data Science for Global Health /
spellingShingle Leveraging Data Science for Global Health /
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.
title_full Leveraging Data Science for Global Health / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai.
title_fullStr Leveraging Data Science for Global Health / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai.
title_full_unstemmed Leveraging Data Science for Global Health / edited by Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai.
title_auth Leveraging Data Science for Global Health /
title_new Leveraging Data Science for Global Health /
title_sort leveraging data science for global health /
publisher Springer Nature
Springer International Publishing : Imprint: Springer,
publishDate 2020
physical 1 online resource (XII, 475 p. 196 illus., 175 illus. in color.)
edition 1st ed. 2020.
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.
isbn 3-030-47994-3
3-030-47993-5
callnumber-first R - Medicine
callnumber-subject R - General Medicine
callnumber-label R858-859
callnumber-sort R 3858 3859.7
illustrated Not Illustrated
dewey-hundreds 500 - Science
dewey-tens 500 - Science
dewey-ones 502 - Miscellany
dewey-full 502.85
dewey-sort 3502.85
dewey-raw 502.85
dewey-search 502.85
oclc_num 1182515218
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