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
  4. Data for Global Health Projects

    1. Front Matter
      Pages 305-305
    2. Philip Christian C. Zuniga, Susann Roth, Alvin B. Marcelo
      Pages 315-327 Open Access
    3. Richard Kimera, Fred Kaggwa, Rogers Mwavu, Robert Mugonza, Wilson Tumuhimbise, Gloria Munguci et al.
      Pages 329-350 Open Access
    4. Yuan Lai, David J. Stone
      Pages 351-363 Open Access
    5. Yvonne MacPherson, Kathy Pham
      Pages 365-372 Open Access
  5. Case Studies

    1. Front Matter
      Pages 383-383
    2. Pragati Jaiswal, Amber Nigam, Teertha Arora, Uma Girkar, Leo Anthony Celi, Kenneth E. Paik
      Pages 397-416 Open Access
    3. Shalen De Silva, Ramya Pinnamaneni, Kavya Ravichandran, Alaa Fadaq, Yun Mei, Vincent Sin
      Pages 417-428 Open Access
    4. Patrick McSharry, Andre Prawira Putra, Rachel Shin, Olivia Mae Waring, Maiamuna S. Majumder, Ned McCague et al.
      Pages 429-441 Open Access
    5. Michael Morley, Maiamuna S. Majumder, Tony Gallanis, Joseph Wilson
      Pages 443-452 Open Access
    6. Patricia Ordóñez Franco, María Eglée Pérez Hernández, Humberto Ortiz-Zuazaga, José García Arrarás
      Pages 453-467 Open Access
  6. Back Matter
    Pages 469-475

About this book


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.


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

Bibliographic information