Skip to main content
Top
Published in: KI - Künstliche Intelligenz 2/2015

01-06-2015 | Discussion

Revolution in Health and Wellbeing

Machine Learning, Crowdsourcing and Self-annotation

Author: András Lőrincz

Published in: KI - Künstliche Intelligenz | Issue 2/2015

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

KI - Künstliche Intelligenz

The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society - with constributions from troughout the field of artificial intelligence.

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Show more products
Literature
1.
go back to reference Avidan S, Butman M (2006) Blind vision. In: Computer vision-ECCV 2006, Springer pp 1–13 Avidan S, Butman M (2006) Blind vision. In: Computer vision-ECCV 2006, Springer pp 1–13
3.
go back to reference Doan A, Ramakrishnan R, Halevy AY (2011) Crowdsourcing systems on the world-wide web. Comm ACM 54(4):86–96CrossRef Doan A, Ramakrishnan R, Halevy AY (2011) Crowdsourcing systems on the world-wide web. Comm ACM 54(4):86–96CrossRef
4.
go back to reference Dua S, Acharya UR, Dua P (2014) Machine learning in healthcare informatics. Springer, BerlinCrossRef Dua S, Acharya UR, Dua P (2014) Machine learning in healthcare informatics. Springer, BerlinCrossRef
6.
go back to reference Kiefer AW, Rhea CK, Warren WH (2013) Vr-based assessment and rehabilitation of functional mobility. In: Human walking in virtual environments, Springer, New York pp 333–350 Kiefer AW, Rhea CK, Warren WH (2013) Vr-based assessment and rehabilitation of functional mobility. In: Human walking in virtual environments, Springer, New York pp 333–350
7.
go back to reference Kingma DP, Mohamed S, Rezende DJ, Welling M (2014) Semi-supervised learning with deep generative models. In: Advanced neural information processing system pp 3581–3589 Kingma DP, Mohamed S, Rezende DJ, Welling M (2014) Semi-supervised learning with deep generative models. In: Advanced neural information processing system pp 3581–3589
8.
go back to reference Lőrincz A (2008) Machine situation assessment and assistance. In: Proceedings of regional conference on embedded and ambient system. John von Neumann Computer Society, pp 61–68 Lőrincz A (2008) Machine situation assessment and assistance. In: Proceedings of regional conference on embedded and ambient system. John von Neumann Computer Society, pp 61–68
9.
go back to reference Lőrincz A, Takács D (2011) AGI architecture measures human parameters and optimizes human performance. In: Artificial general intelligence, Springer, pp 321–326 Lőrincz A, Takács D (2011) AGI architecture measures human parameters and optimizes human performance. In: Artificial general intelligence, Springer, pp 321–326
10.
go back to reference Mayer J, Johnson T (1988) Picture communication symbols. Mayer-Johnson, Solana Beach Mayer J, Johnson T (1988) Picture communication symbols. Mayer-Johnson, Solana Beach
11.
go back to reference Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117CrossRef Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117CrossRef
13.
go back to reference Taati B, Snoek J, Aleman D, Ghavamzadeh A (2014) Data mining in bone marrow transplant records to identify patients with high odds of survival. Biomed Health Inform IEEE J 18(1):21–27 Taati B, Snoek J, Aleman D, Ghavamzadeh A (2014) Data mining in bone marrow transplant records to identify patients with high odds of survival. Biomed Health Inform IEEE J 18(1):21–27
14.
go back to reference Vörös G, Verő A, Pintér B, Miksztai-Réthey B, Toyama T, Lőrincz A, Sonntag D (2014) Towards a smart wearable tool to enable people with sspi to communicate by sentence fragments. In: Pervasive computing paradigms for mental health, Springer, pp 90–99 Vörös G, Verő A, Pintér B, Miksztai-Réthey B, Toyama T, Lőrincz A, Sonntag D (2014) Towards a smart wearable tool to enable people with sspi to communicate by sentence fragments. In: Pervasive computing paradigms for mental health, Springer, pp 90–99
15.
go back to reference Ziegler G, Farkas C, Lőrincz A (2006) A framework for anonymous but accountable self-organizing communities. Inform Softw Technol 48(8):726–744CrossRef Ziegler G, Farkas C, Lőrincz A (2006) A framework for anonymous but accountable self-organizing communities. Inform Softw Technol 48(8):726–744CrossRef
Metadata
Title
Revolution in Health and Wellbeing
Machine Learning, Crowdsourcing and Self-annotation
Author
András Lőrincz
Publication date
01-06-2015
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2/2015
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-015-0366-z

Other articles of this Issue 2/2015

KI - Künstliche Intelligenz 2/2015 Go to the issue

Premium Partner