This paper is in the following e-collection/theme issue:

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1570)

Published on in Vol 15, No 1 (2013): January

Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network

Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network

Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network

Authors of this article:

Max Little1 ;   Paul Wicks2 ;   Timothy Vaughan2 ;   Alex Pentland1
Article Authors Cited by (30) Tweetations (24) Metrics

Max Little   1 , B.Sc (Hons), PhD ;   Paul Wicks   2 , PhD ;   Timothy Vaughan   2 , PhD ;   Alex Pentland   1 , PhD

1 Human Dynamics Group, Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States

2 Research and Development, PatientsLikeMe Inc., Cambridge, MA, United States

Corresponding Author:

  • Max Little, B.Sc (Hons), PhD
  • Human Dynamics Group
  • Media Lab
  • Massachusetts Institute of Technology
  • 77 Massachusetts Avenue
  • Cambridge, MA, 02139
  • United States
  • Phone: 1 617-253-1000
  • Fax: 1 617-253-1000
  • Email: maxl@mit.edu