Revolution in Health and Wellbeing: Machine Learning, Crowdsourcing and Self-annotation

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We argue that recent technology developments hold great promises for health and wellbeing. In our view, recent advances of (1) smart tools and wearable sensors of diverse kinds, (2) data collection and data mining methods, (3) 3D visual recording and visual processing methods, (4) 3D models of the environment with robust physics engine, and last but not least, (5) new applications of human computing and crowdsourcing started the revolution. We are neither claiming nor excluding that human intelligence will be reached in some years from now, but make the above claim, which is both weaker and stronger. We believe that fast developments for health and wellbeing are the question of active collaboration between health and wellbeing experts and motivated engineers.

Original languageEnglish
Pages (from-to)219-222
Number of pages4
JournalKI - Kunstliche Intelligenz
Volume29
Issue number2
DOIs
Publication statusPublished - Jun 1 2015

Keywords

  • Crowdsourcing
  • Data mining
  • Machine learning
  • Personalization
  • Smart tools

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Revolution in Health and Wellbeing: Machine Learning, Crowdsourcing and Self-annotation'. Together they form a unique fingerprint.

  • Cite this