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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1275)

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 Little 1 ;   Paul Wicks 2 ;   Timothy Vaughan 2 ;   Alex Pentland 1
Article Authors Cited by (27) Tweetations (25) 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 , US

2 Research and Development , PatientsLikeMe Inc. , Cambridge , MA , US

Corresponding Author:

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