Advertisement

© 2020

Leveraging Data Science for Global Health

  • Leo Anthony Celi
  • Maimuna S. Majumder
  • Patricia Ordóñez
  • Juan Sebastian Osorio
  • Kenneth E. Paik
  • Melek Somai

Benefits

  • Is the first and currently the only book on digital disease surveillance through the application of machine learning to non-traditional data sources

  • Focuses on combating disease and promoting health, especially in resource-constrained settings

  • Includes and expands on the latest non-traditional data sources such as Google Trends, Google Street View, the news media, and social media

  • Is an open access book

Open Access
Textbook

Table of contents

  1. Front Matter
    Pages i-xii
  2. Building a Data Science Ecosystem for Healthcare

    1. Front Matter
      Pages 1-1
    2. Lucas Bulgarelli, Antonio Núñez-Reiz, Rodrigo Octavio Deliberato
      Pages 55-64 Open Access
    3. Katharine Morley, Michael Morley, Andrea Beratarrechea
      Pages 65-75 Open Access
    4. Gary Lin, Michele Palopoli, Viva Dadwal
      Pages 77-98 Open Access
    5. Philip Christian C. Zuniga, Rose Ann C. Zuniga, Marie Jo-anne Mendoza, Ada Angeli Cariaga, Raymond Francis Sarmiento, Alvin B. Marcelo
      Pages 99-107 Open Access
  3. Health Data Science Workshops

    1. Front Matter
      Pages 109-109
    2. Calvin J. Chiew
      Pages 111-128 Open Access
    3. Cátia M. Salgado, Susana M. Vieira
      Pages 169-198 Open Access
    4. Wei-Hung Weng
      Pages 199-217 Open Access
    5. Siqi Liu, Hao Du, Mengling Feng
      Pages 219-228 Open Access
    6. Leo Anthony Celi, Christina Chen, Daniel Gruhl, Chaitanya Shivade, Joy Tzung-Yu Wu
      Pages 229-250 Open Access
    7. Olivia Mae Waring, Maiamuna S. Majumder
      Pages 251-261 Open Access
    8. Chen Xie
      Pages 285-303 Open Access

About this book

Introduction

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

Open Access Big Data Machine Learning Artificial Intelligence Health Informatics Digital Disease Surveillance Health Mapping Health Records for Non-Communicable Diseases HealthMap Tools for Clinical Trials

Editors and affiliations

  • Leo Anthony Celi
    • 1
  • Maimuna S. Majumder
    • 2
  • Patricia Ordóñez
    • 3
  • Juan Sebastian Osorio
    • 4
  • Kenneth E. Paik
    • 5
  • Melek Somai
    • 6
  1. 1.Massachusetts Institute of TechnologyCambridgeUSA
  2. 2.Boston Children’s HospitalHarvard Medical SchoolBostonUSA
  3. 3.University of Puerto Rico Río PiedrasSan JuanUSA
  4. 4.ScienteLab, Department of Global HealthUniversity of WashingtonSeattleUSA
  5. 5.Institute for Medical Engineering and ScienceMassachusetts Institute of TechnologyCambridgeUSA
  6. 6.Imperial College LondonLondonUK

About the editors

Leo Anthony Celi, M.D., M.S., M.P.H., has practiced medicine in three continents, giving him broad perspectives in healthcare delivery. As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology (LCP) and as an attending physician at the Beth Israel Deaconess Medical Center (BIDMC), he brings together clinicians and data scientists to support research using data routinely collected in the process of care. Leo also founded and co-directs Sana, a cross-disciplinary organization based at the Institute for Medical Engineering and Science at MIT, whose objective is to leverage information technology to improve health outcomes in low- and middle-income countries. He is one of the course directors for global health informatics to improve quality of care, and collaborative data science in medicine, both at MIT. He is an editor of the textbook for each course, both released under an open access license. Leo has spoken in 25 countries about the value of data in improving health outcomes. 

Bibliographic information

  • Book Title Leveraging Data Science for Global Health
  • Editors Leo Anthony Celi
    Maimuna S. Majumder
    Patricia Ordóñez
    Juan Sebastian Osorio
    Kenneth E. Paik
    Melek Somai
  • DOI https://doi.org/10.1007/978-3-030-47994-7
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2020
  • License CC BY
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Hardcover ISBN 978-3-030-47993-0
  • Softcover ISBN 978-3-030-47996-1
  • eBook ISBN 978-3-030-47994-7
  • Edition Number 1
  • Number of Pages XII, 475
  • Number of Illustrations 21 b/w illustrations, 175 illustrations in colour
  • Topics Health Informatics
    Health Informatics
    Health Economics
  • Buy this book on publisher's site