Table of contents

  1. Front Matter
    Pages i-xxi
  2. Setting the Stage: Rationale Behind and Challenges to Health Data Analysis

    1. Front Matter
      Pages 1-2
    2. Sharukh Lokhandwala, Barret Rush
      Pages 3-7 Open Access
    3. Jeff Marshall, Abdullah Chahin, Barret Rush
      Pages 9-16 Open Access
    4. Sunil Nair, Douglas Hsu, Leo Anthony Celi
      Pages 17-26 Open Access
    5. David Stone, Justin Rousseau, Yuan Lai
      Pages 27-42 Open Access
    6. Roger Mark
      Pages 43-49 Open Access
    7. Yuan Lai, Edward Moseley, Francisco Salgueiro, David Stone
      Pages 51-60 Open Access
    8. Laura Myers, Jennifer Stevens
      Pages 61-70 Open Access
    9. John Danziger, Andrew J. Zimolzak
      Pages 71-78 Open Access
  3. A Cookbook: From Research Question Formulation to Validation of Findings

    1. Front Matter
      Pages 79-80
    2. Anuj Mehta, Brian Malley, Allan Walkey
      Pages 81-92 Open Access
    3. Ari Moskowitz, Kenneth Chen
      Pages 93-100 Open Access
    4. Tom Pollard, Franck Dernoncourt, Samuel Finlayson, Adrian Velasquez
      Pages 101-114 Open Access
    5. Brian Malley, Daniele Ramazzotti, Joy Tzung-yu Wu
      Pages 115-141 Open Access
    6. Cátia M. Salgado, Carlos Azevedo, Hugo Proença, Susana M. Vieira
      Pages 143-162 Open Access
    7. Cátia M. Salgado, Carlos Azevedo, Hugo Proença, Susana M. Vieira
      Pages 163-183 Open Access
    8. Matthieu Komorowski, Dominic C. Marshall, Justin D. Salciccioli, Yves Crutain
      Pages 185-203 Open Access
    9. Jesse D. Raffa, Marzyeh Ghassemi, Tristan Naumann, Mengling Feng, Douglas Hsu
      Pages 205-261 Open Access
    10. Justin D. Salciccioli, Yves Crutain, Matthieu Komorowski, Dominic C. Marshall
      Pages 263-271 Open Access
  4. Case Studies Using MIMIC

    1. Front Matter
      Pages 273-274
    2. Anuj Mehta, Franck Dernoncourt, Allan Walkey
      Pages 275-283 Open Access
    3. Nicolás Della Penna, Jennifer P. Stevens, Robert Stretch
      Pages 285-294 Open Access
    4. Joon Lee, Joel A. Dubin, David M. Maslove
      Pages 315-324 Open Access
    5. Peter H. Charlton, Marco Pimentel, Sharukh Lokhandwala
      Pages 325-338 Open Access
    6. Kenneth P. Chen, Ari Moskowitz
      Pages 339-349 Open Access
    7. Matthieu Komorowski, Jesse Raffa
      Pages 351-367 Open Access
    8. Li-wei H. Lehman, Mengling Feng, Yijun Yang, Roger G. Mark
      Pages 369-375 Open Access
    9. Peter H. Charlton, Mauricio Villarroel, Francisco Salguiero
      Pages 377-390 Open Access
    10. Qiao Li, Gari D. Clifford
      Pages 391-403 Open Access
    11. Raymond Francis Sarmiento, Franck Dernoncourt
      Pages 405-417 Open Access
    12. Franck Dernoncourt, Shamim Nemati, Elias Baedorf Kassis, Mohammad Mahdi Ghassemi
      Pages 419-427 Open Access
  5. MIT Critical Data
    Pages E1-E1 Open Access

About this book


This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. 

Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence.

The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.


analysis of waveform data computer science and artificial intelligence data extraction and preprocessing data mining decision and cost effectiveness analysis diagnostic and therap electronic health records intensive care and emergency medicine learning healthcare system machine learning medical internet research objectives of secondary analysis pharmacovigilance predictive modeling review of clinical databse secondary analysis shared decision making with patience signal processing validation and sensitivity

Authors and affiliations

  • MIT Critical Data
    • 1
  1. 1.Massachusetts Institute of TechnologyCambridgeUSA

Bibliographic information

  • DOI
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Medicine Medicine (R0)
  • Print ISBN 978-3-319-43740-8
  • Online ISBN 978-3-319-43742-2
  • Buy this book on publisher's site